| | |
- __builtin__.object
-
- broadcast
- dtype
- flatiter
- generic
-
- bool_
- bool_
- flexible
-
- character
-
- string_(__builtin__.str, character)
- string_(__builtin__.str, character)
- string_(__builtin__.str, character)
- string_(__builtin__.str, character)
- unicode_(__builtin__.unicode, character)
- unicode_(__builtin__.unicode, character)
- void
-
- numpy.core.records.record
- void
-
- numpy.core.records.record
- number
-
- inexact
-
- complexfloating
-
- complex128(complexfloating, __builtin__.complex)
- complex128(complexfloating, __builtin__.complex)
- complex128(complexfloating, __builtin__.complex)
- complex128(complexfloating, __builtin__.complex)
- complex256
- complex256
- complex256
- complex256
- complex64
- complex64
- complex64
- floating
-
- float128
- float128
- float128
- float32
- float32
- float64(floating, __builtin__.float)
- float64(floating, __builtin__.float)
- float64(floating, __builtin__.float)
- integer
-
- signedinteger
-
- int16
- int16
- int32
- int32
- int64(signedinteger, __builtin__.int)
- int64(signedinteger, __builtin__.int)
- int64(signedinteger, __builtin__.int)
- int64(signedinteger, __builtin__.int)
- int64(signedinteger, __builtin__.int)
- int8
- int8
- unsignedinteger
-
- uint16
- uint16
- uint32
- uint32
- uint64
- uint64
- uint64
- uint64
- uint64
- uint8
- uint8
- object_
- object_
- ndarray
-
- numpy.core.defchararray.chararray
- numpy.core.memmap.memmap
- numpy.core.records.recarray
- numpy.matrixlib.defmatrix.matrix
- ufunc
- numpy.core.getlimits.finfo
- numpy.core.machar.MachAr
- numpy.core.numeric.errstate
- numpy.lib._datasource.DataSource
- numpy.lib.function_base.vectorize
- numpy.lib.index_tricks.ndenumerate
- numpy.lib.index_tricks.ndindex
- numpy.lib.polynomial.poly1d
- __builtin__.str(__builtin__.basestring)
-
- string_(__builtin__.str, character)
- string_(__builtin__.str, character)
- string_(__builtin__.str, character)
- string_(__builtin__.str, character)
- __builtin__.unicode(__builtin__.basestring)
-
- unicode_(__builtin__.unicode, character)
- unicode_(__builtin__.unicode, character)
- exceptions.RuntimeWarning(exceptions.Warning)
-
- numpy.core.numeric.ComplexWarning
- exceptions.UserWarning(exceptions.Warning)
-
- numpy.lib.polynomial.RankWarning
- numpy._import_tools.PackageLoader
- numpy.core.getlimits.iinfo
- numpy.core.records.format_parser
class DataSource(__builtin__.object) |
| |
DataSource(destpath='.')
A generic data source file (file, http, ftp, ...).
DataSources can be local files or remote files/URLs. The files may
also be compressed or uncompressed. DataSource hides some of the low-level
details of downloading the file, allowing you to simply pass in a valid
file path (or URL) and obtain a file object.
Parameters
----------
destpath : str or None, optional
Path to the directory where the source file gets downloaded to for use.
If `destpath` is None, a temporary directory will be created.
The default path is the current directory.
Notes
-----
URLs require a scheme string (``http://``) to be used, without it they
will fail::
>>> repos = DataSource()
>>> repos.exists('www.google.com/index.html')
False
>>> repos.exists('http://www.google.com/index.html')
True
Temporary directories are deleted when the DataSource is deleted.
Examples
--------
::
>>> ds = DataSource('/home/guido')
>>> urlname = 'http://www.google.com/index.html'
>>> gfile = ds.open('http://www.google.com/index.html') # remote file
>>> ds.abspath(urlname)
'/home/guido/www.google.com/site/index.html'
>>> ds = DataSource(None) # use with temporary file
>>> ds.open('/home/guido/foobar.txt')
<open file '/home/guido.foobar.txt', mode 'r' at 0x91d4430>
>>> ds.abspath('/home/guido/foobar.txt')
'/tmp/tmpy4pgsP/home/guido/foobar.txt'
|
| |
Methods defined here:
- __del__(self)
- __init__(self, destpath='.')
- Create a DataSource with a local path at destpath.
- abspath(self, path)
- Return absolute path of file in the DataSource directory.
If `path` is an URL, then `abspath` will return either the location
the file exists locally or the location it would exist when opened
using the `open` method.
Parameters
----------
path : str
Can be a local file or a remote URL.
Returns
-------
out : str
Complete path, including the `DataSource` destination directory.
Notes
-----
The functionality is based on `os.path.abspath`.
- exists(self, path)
- Test if path exists.
Test if `path` exists as (and in this order):
- a local file.
- a remote URL that has been downloaded and stored locally in the
`DataSource` directory.
- a remote URL that has not been downloaded, but is valid and accessible.
Parameters
----------
path : str
Can be a local file or a remote URL.
Returns
-------
out : bool
True if `path` exists.
Notes
-----
When `path` is an URL, `exists` will return True if it's either stored
locally in the `DataSource` directory, or is a valid remote URL.
`DataSource` does not discriminate between the two, the file is accessible
if it exists in either location.
- open(self, path, mode='r')
- Open and return file-like object.
If `path` is an URL, it will be downloaded, stored in the `DataSource`
directory and opened from there.
Parameters
----------
path : str
Local file path or URL to open.
mode : {'r', 'w', 'a'}, optional
Mode to open `path`. Mode 'r' for reading, 'w' for writing, 'a' to
append. Available modes depend on the type of object specified by
`path`. Default is 'r'.
Returns
-------
out : file object
File object.
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
|
class MachAr(__builtin__.object) |
| |
Diagnosing machine parameters.
Attributes
----------
ibeta : int
Radix in which numbers are represented.
it : int
Number of base-`ibeta` digits in the floating point mantissa M.
machep : int
Exponent of the smallest (most negative) power of `ibeta` that,
added to 1.0, gives something different from 1.0
eps : float
Floating-point number ``beta**machep`` (floating point precision)
negep : int
Exponent of the smallest power of `ibeta` that, substracted
from 1.0, gives something different from 1.0.
epsneg : float
Floating-point number ``beta**negep``.
iexp : int
Number of bits in the exponent (including its sign and bias).
minexp : int
Smallest (most negative) power of `ibeta` consistent with there
being no leading zeros in the mantissa.
xmin : float
Floating point number ``beta**minexp`` (the smallest [in
magnitude] usable floating value).
maxexp : int
Smallest (positive) power of `ibeta` that causes overflow.
xmax : float
``(1-epsneg) * beta**maxexp`` (the largest [in magnitude]
usable floating value).
irnd : int
In ``range(6)``, information on what kind of rounding is done
in addition, and on how underflow is handled.
ngrd : int
Number of 'guard digits' used when truncating the product
of two mantissas to fit the representation.
epsilon : float
Same as `eps`.
tiny : float
Same as `xmin`.
huge : float
Same as `xmax`.
precision : float
``- int(-log10(eps))``
resolution : float
``- 10**(-precision)``
Parameters
----------
float_conv : function, optional
Function that converts an integer or integer array to a float
or float array. Default is `float`.
int_conv : function, optional
Function that converts a float or float array to an integer or
integer array. Default is `int`.
float_to_float : function, optional
Function that converts a float array to float. Default is `float`.
Note that this does not seem to do anything useful in the current
implementation.
float_to_str : function, optional
Function that converts a single float to a string. Default is
``lambda v:'%24.16e' %v``.
title : str, optional
Title that is printed in the string representation of `MachAr`.
See Also
--------
finfo : Machine limits for floating point types.
iinfo : Machine limits for integer types.
References
----------
.. [1] Press, Teukolsky, Vetterling and Flannery,
"Numerical Recipes in C++," 2nd ed,
Cambridge University Press, 2002, p. 31.
|
| |
Methods defined here:
- __init__(self, float_conv=<type 'float'>, int_conv=<type 'int'>, float_to_float=<type 'float'>, float_to_str=<function <lambda>>, title='Python floating point number')
- float_conv - convert integer to float (array)
int_conv - convert float (array) to integer
float_to_float - convert float array to float
float_to_str - convert array float to str
title - description of used floating point numbers
- __str__(self)
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
|
class PackageLoader |
| | |
Methods defined here:
- __call__(self, *packages, **options)
- Load one or more packages into parent package top-level namespace.
This function is intended to shorten the need to import many
subpackages, say of scipy, constantly with statements such as
import scipy.linalg, scipy.fftpack, scipy.etc...
Instead, you can say:
import scipy
scipy.pkgload('linalg','fftpack',...)
or
scipy.pkgload()
to load all of them in one call.
If a name which doesn't exist in scipy's namespace is
given, a warning is shown.
Parameters
----------
*packages : arg-tuple
the names (one or more strings) of all the modules one
wishes to load into the top-level namespace.
verbose= : integer
verbosity level [default: -1].
verbose=-1 will suspend also warnings.
force= : bool
when True, force reloading loaded packages [default: False].
postpone= : bool
when True, don't load packages [default: False]
- __init__(self, verbose=False, infunc=False)
- Manages loading packages.
- error(self, mess)
- get_pkgdocs(self)
- Return documentation summary of subpackages.
- log(self, mess)
- warn(self, mess)
|
bool8 = class bool_(generic) |
| |
Numpy's Boolean type. Character code: ``?``. Alias: bool8
|
| |
- Method resolution order:
- bool_
- generic
- __builtin__.object
Methods defined here:
- __and__(...)
- x.__and__(y) <==> x&y
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __rand__(...)
- x.__rand__(y) <==> y&x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __xor__(...)
- x.__xor__(y) <==> x^y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __oct__(...)
- x.__oct__() <==> oct(x)
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class bool_(generic) |
| |
Numpy's Boolean type. Character code: ``?``. Alias: bool8
|
| |
- Method resolution order:
- bool_
- generic
- __builtin__.object
Methods defined here:
- __and__(...)
- x.__and__(y) <==> x&y
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __rand__(...)
- x.__rand__(y) <==> y&x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __xor__(...)
- x.__xor__(y) <==> x^y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __oct__(...)
- x.__oct__() <==> oct(x)
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class broadcast(__builtin__.object) |
| |
Produce an object that mimics broadcasting.
Parameters
----------
in1, in2, ... : array_like
Input parameters.
Returns
-------
b : broadcast object
Broadcast the input parameters against one another, and
return an object that encapsulates the result.
Amongst others, it has ``shape`` and ``nd`` properties, and
may be used as an iterator.
Examples
--------
Manually adding two vectors, using broadcasting:
>>> x = np.array([[1], [2], [3]])
>>> y = np.array([4, 5, 6])
>>> b = np.broadcast(x, y)
>>> out = np.empty(b.shape)
>>> out.flat = [u+v for (u,v) in b]
>>> out
array([[ 5., 6., 7.],
[ 6., 7., 8.],
[ 7., 8., 9.]])
Compare against built-in broadcasting:
>>> x + y
array([[5, 6, 7],
[6, 7, 8],
[7, 8, 9]])
|
| |
Methods defined here:
- __iter__(...)
- x.__iter__() <==> iter(x)
- next(...)
- x.next() -> the next value, or raise StopIteration
- reset(...)
Data descriptors defined here:
- index
- current index in broadcasted result
Examples
--------
>>> x = np.array([[1], [2], [3]])
>>> y = np.array([4, 5, 6])
>>> b = np.broadcast(x, y)
>>> b.index
0
>>> b.next(), b.next(), b.next()
((1, 4), (1, 5), (1, 6))
>>> b.index
3
- iters
- tuple of iterators along ``self``'s "components."
Returns a tuple of `numpy.flatiter` objects, one for each "component"
of ``self``.
See Also
--------
numpy.flatiter
Examples
--------
>>> x = np.array([1, 2, 3])
>>> y = np.array([[4], [5], [6]])
>>> b = np.broadcast(x, y)
>>> row, col = b.iters
>>> row.next(), col.next()
(1, 4)
- nd
- Number of dimensions of broadcasted result.
Examples
--------
>>> x = np.array([1, 2, 3])
>>> y = np.array([[4], [5], [6]])
>>> b = np.broadcast(x, y)
>>> b.nd
2
- numiter
- Number of iterators possessed by the broadcasted result.
Examples
--------
>>> x = np.array([1, 2, 3])
>>> y = np.array([[4], [5], [6]])
>>> b = np.broadcast(x, y)
>>> b.numiter
2
- shape
- Shape of broadcasted result.
Examples
--------
>>> x = np.array([1, 2, 3])
>>> y = np.array([[4], [5], [6]])
>>> b = np.broadcast(x, y)
>>> b.shape
(3, 3)
- size
- Total size of broadcasted result.
Examples
--------
>>> x = np.array([1, 2, 3])
>>> y = np.array([[4], [5], [6]])
>>> b = np.broadcast(x, y)
>>> b.size
9
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
|
byte = class int8(signedinteger) |
| |
8-bit integer. Character code ``b``. C char compatible.
|
| |
- Method resolution order:
- int8
- signedinteger
- integer
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
bytes_ = class string_(__builtin__.str, character) |
| | |
- Method resolution order:
- string_
- __builtin__.str
- __builtin__.basestring
- character
- flexible
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from __builtin__.str:
- __add__(...)
- x.__add__(y) <==> x+y
- __contains__(...)
- x.__contains__(y) <==> y in x
- __format__(...)
- S.__format__(format_spec) -> string
Return a formatted version of S as described by format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __getnewargs__(...)
- __getslice__(...)
- x.__getslice__(i, j) <==> x[i:j]
Use of negative indices is not supported.
- __len__(...)
- x.__len__() <==> len(x)
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(n) <==> x*n
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(n) <==> n*x
- __sizeof__(...)
- S.__sizeof__() -> size of S in memory, in bytes
- capitalize(...)
- S.capitalize() -> string
Return a copy of the string S with only its first character
capitalized.
- center(...)
- S.center(width[, fillchar]) -> string
Return S centered in a string of length width. Padding is
done using the specified fill character (default is a space)
- count(...)
- S.count(sub[, start[, end]]) -> int
Return the number of non-overlapping occurrences of substring sub in
string S[start:end]. Optional arguments start and end are interpreted
as in slice notation.
- decode(...)
- S.decode([encoding[,errors]]) -> object
Decodes S using the codec registered for encoding. encoding defaults
to the default encoding. errors may be given to set a different error
handling scheme. Default is 'strict' meaning that encoding errors raise
a UnicodeDecodeError. Other possible values are 'ignore' and 'replace'
as well as any other name registered with codecs.register_error that is
able to handle UnicodeDecodeErrors.
- encode(...)
- S.encode([encoding[,errors]]) -> object
Encodes S using the codec registered for encoding. encoding defaults
to the default encoding. errors may be given to set a different error
handling scheme. Default is 'strict' meaning that encoding errors raise
a UnicodeEncodeError. Other possible values are 'ignore', 'replace' and
'xmlcharrefreplace' as well as any other name registered with
codecs.register_error that is able to handle UnicodeEncodeErrors.
- endswith(...)
- S.endswith(suffix[, start[, end]]) -> bool
Return True if S ends with the specified suffix, False otherwise.
With optional start, test S beginning at that position.
With optional end, stop comparing S at that position.
suffix can also be a tuple of strings to try.
- expandtabs(...)
- S.expandtabs([tabsize]) -> string
Return a copy of S where all tab characters are expanded using spaces.
If tabsize is not given, a tab size of 8 characters is assumed.
- find(...)
- S.find(sub [,start [,end]]) -> int
Return the lowest index in S where substring sub is found,
such that sub is contained within s[start:end]. Optional
arguments start and end are interpreted as in slice notation.
Return -1 on failure.
- format(...)
- S.format(*args, **kwargs) -> string
Return a formatted version of S, using substitutions from args and kwargs.
The substitutions are identified by braces ('{' and '}').
- index(...)
- S.index(sub [,start [,end]]) -> int
Like S.find() but raise ValueError when the substring is not found.
- isalnum(...)
- S.isalnum() -> bool
Return True if all characters in S are alphanumeric
and there is at least one character in S, False otherwise.
- isalpha(...)
- S.isalpha() -> bool
Return True if all characters in S are alphabetic
and there is at least one character in S, False otherwise.
- isdigit(...)
- S.isdigit() -> bool
Return True if all characters in S are digits
and there is at least one character in S, False otherwise.
- islower(...)
- S.islower() -> bool
Return True if all cased characters in S are lowercase and there is
at least one cased character in S, False otherwise.
- isspace(...)
- S.isspace() -> bool
Return True if all characters in S are whitespace
and there is at least one character in S, False otherwise.
- istitle(...)
- S.istitle() -> bool
Return True if S is a titlecased string and there is at least one
character in S, i.e. uppercase characters may only follow uncased
characters and lowercase characters only cased ones. Return False
otherwise.
- isupper(...)
- S.isupper() -> bool
Return True if all cased characters in S are uppercase and there is
at least one cased character in S, False otherwise.
- join(...)
- S.join(iterable) -> string
Return a string which is the concatenation of the strings in the
iterable. The separator between elements is S.
- ljust(...)
- S.ljust(width[, fillchar]) -> string
Return S left-justified in a string of length width. Padding is
done using the specified fill character (default is a space).
- lower(...)
- S.lower() -> string
Return a copy of the string S converted to lowercase.
- lstrip(...)
- S.lstrip([chars]) -> string or unicode
Return a copy of the string S with leading whitespace removed.
If chars is given and not None, remove characters in chars instead.
If chars is unicode, S will be converted to unicode before stripping
- partition(...)
- S.partition(sep) -> (head, sep, tail)
Search for the separator sep in S, and return the part before it,
the separator itself, and the part after it. If the separator is not
found, return S and two empty strings.
- replace(...)
- S.replace(old, new[, count]) -> string
Return a copy of string S with all occurrences of substring
old replaced by new. If the optional argument count is
given, only the first count occurrences are replaced.
- rfind(...)
- S.rfind(sub [,start [,end]]) -> int
Return the highest index in S where substring sub is found,
such that sub is contained within s[start:end]. Optional
arguments start and end are interpreted as in slice notation.
Return -1 on failure.
- rindex(...)
- S.rindex(sub [,start [,end]]) -> int
Like S.rfind() but raise ValueError when the substring is not found.
- rjust(...)
- S.rjust(width[, fillchar]) -> string
Return S right-justified in a string of length width. Padding is
done using the specified fill character (default is a space)
- rpartition(...)
- S.rpartition(sep) -> (head, sep, tail)
Search for the separator sep in S, starting at the end of S, and return
the part before it, the separator itself, and the part after it. If the
separator is not found, return two empty strings and S.
- rsplit(...)
- S.rsplit([sep [,maxsplit]]) -> list of strings
Return a list of the words in the string S, using sep as the
delimiter string, starting at the end of the string and working
to the front. If maxsplit is given, at most maxsplit splits are
done. If sep is not specified or is None, any whitespace string
is a separator.
- rstrip(...)
- S.rstrip([chars]) -> string or unicode
Return a copy of the string S with trailing whitespace removed.
If chars is given and not None, remove characters in chars instead.
If chars is unicode, S will be converted to unicode before stripping
- split(...)
- S.split([sep [,maxsplit]]) -> list of strings
Return a list of the words in the string S, using sep as the
delimiter string. If maxsplit is given, at most maxsplit
splits are done. If sep is not specified or is None, any
whitespace string is a separator and empty strings are removed
from the result.
- splitlines(...)
- S.splitlines([keepends]) -> list of strings
Return a list of the lines in S, breaking at line boundaries.
Line breaks are not included in the resulting list unless keepends
is given and true.
- startswith(...)
- S.startswith(prefix[, start[, end]]) -> bool
Return True if S starts with the specified prefix, False otherwise.
With optional start, test S beginning at that position.
With optional end, stop comparing S at that position.
prefix can also be a tuple of strings to try.
- strip(...)
- S.strip([chars]) -> string or unicode
Return a copy of the string S with leading and trailing
whitespace removed.
If chars is given and not None, remove characters in chars instead.
If chars is unicode, S will be converted to unicode before stripping
- swapcase(...)
- S.swapcase() -> string
Return a copy of the string S with uppercase characters
converted to lowercase and vice versa.
- title(...)
- S.title() -> string
Return a titlecased version of S, i.e. words start with uppercase
characters, all remaining cased characters have lowercase.
- translate(...)
- S.translate(table [,deletechars]) -> string
Return a copy of the string S, where all characters occurring
in the optional argument deletechars are removed, and the
remaining characters have been mapped through the given
translation table, which must be a string of length 256.
- upper(...)
- S.upper() -> string
Return a copy of the string S converted to uppercase.
- zfill(...)
- S.zfill(width) -> string
Pad a numeric string S with zeros on the left, to fill a field
of the specified width. The string S is never truncated.
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
cdouble = class complex128(complexfloating, __builtin__.complex) |
| |
Composed of two 64 bit floats
|
| |
- Method resolution order:
- complex128
- complexfloating
- inexact
- number
- generic
- __builtin__.complex
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.complex:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- complex.__format__() -> str
Converts to a string according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
|
cfloat = class complex128(complexfloating, __builtin__.complex) |
| |
Composed of two 64 bit floats
|
| |
- Method resolution order:
- complex128
- complexfloating
- inexact
- number
- generic
- __builtin__.complex
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.complex:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- complex.__format__() -> str
Converts to a string according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
|
class character(flexible) |
| | |
- Method resolution order:
- character
- flexible
- generic
- __builtin__.object
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class chararray(numpy.ndarray) |
| |
chararray(shape, itemsize=1, unicode=False, buffer=None, offset=0,
strides=None, order=None)
Provides a convenient view on arrays of string and unicode values.
.. note::
The `chararray` class exists for backwards compatibility with
Numarray, it is not recommended for new development. Starting from numpy
1.4, if one needs arrays of strings, it is recommended to use arrays of
`dtype` `object_`, `string_` or `unicode_`, and use the free functions
in the `numpy.char` module for fast vectorized string operations.
Versus a regular Numpy array of type `str` or `unicode`, this
class adds the following functionality:
1) values automatically have whitespace removed from the end
when indexed
2) comparison operators automatically remove whitespace from the
end when comparing values
3) vectorized string operations are provided as methods
(e.g. `.endswith`) and infix operators (e.g. ``"+", "*", "%"``)
chararrays should be created using `numpy.char.array` or
`numpy.char.asarray`, rather than this constructor directly.
This constructor creates the array, using `buffer` (with `offset`
and `strides`) if it is not ``None``. If `buffer` is ``None``, then
constructs a new array with `strides` in "C order", unless both
``len(shape) >= 2`` and ``order='Fortran'``, in which case `strides`
is in "Fortran order".
Methods
-------
astype
argsort
copy
count
decode
dump
dumps
encode
endswith
expandtabs
fill
find
flatten
getfield
index
isalnum
isalpha
isdecimal
isdigit
islower
isnumeric
isspace
istitle
isupper
item
join
ljust
lower
lstrip
nonzero
put
ravel
repeat
replace
reshape
resize
rfind
rindex
rjust
rsplit
rstrip
searchsorted
setfield
setflags
sort
split
splitlines
squeeze
startswith
strip
swapaxes
swapcase
take
title
tofile
tolist
tostring
translate
transpose
upper
view
zfill
Parameters
----------
shape : tuple
Shape of the array.
itemsize : int, optional
Length of each array element, in number of characters. Default is 1.
unicode : bool, optional
Are the array elements of type unicode (True) or string (False).
Default is False.
buffer : int, optional
Memory address of the start of the array data. Default is None,
in which case a new array is created.
offset : int, optional
Fixed stride displacement from the beginning of an axis?
Default is 0. Needs to be >=0.
strides : array_like of ints, optional
Strides for the array (see `ndarray.strides` for full description).
Default is None.
order : {'C', 'F'}, optional
The order in which the array data is stored in memory: 'C' ->
"row major" order (the default), 'F' -> "column major"
(Fortran) order.
Examples
--------
>>> charar = np.chararray((3, 3))
>>> charar[:] = 'a'
>>> charar
chararray([['a', 'a', 'a'],
['a', 'a', 'a'],
['a', 'a', 'a']],
dtype='|S1')
>>> charar = np.chararray(charar.shape, itemsize=5)
>>> charar[:] = 'abc'
>>> charar
chararray([['abc', 'abc', 'abc'],
['abc', 'abc', 'abc'],
['abc', 'abc', 'abc']],
dtype='|S5')
|
| |
- Method resolution order:
- chararray
- numpy.ndarray
- __builtin__.object
Methods defined here:
- __add__(self, other)
- Return (self + other), that is string concatenation,
element-wise for a pair of array_likes of str or unicode.
See also
--------
add
- __array_finalize__(self, obj)
- __eq__(self, other)
- Return (self == other) element-wise.
See also
--------
equal
- __ge__(self, other)
- Return (self >= other) element-wise.
See also
--------
greater_equal
- __getitem__(self, obj)
- __gt__(self, other)
- Return (self > other) element-wise.
See also
--------
greater
- __le__(self, other)
- Return (self <= other) element-wise.
See also
--------
less_equal
- __lt__(self, other)
- Return (self < other) element-wise.
See also
--------
less
- __mod__(self, i)
- Return (self % i), that is pre-Python 2.6 string formatting
(iterpolation), element-wise for a pair of array_likes of string_
or unicode_.
See also
--------
mod
- __mul__(self, i)
- Return (self * i), that is string multiple concatenation,
element-wise.
See also
--------
multiply
- __ne__(self, other)
- Return (self != other) element-wise.
See also
--------
not_equal
- __radd__(self, other)
- Return (other + self), that is string concatenation,
element-wise for a pair of array_likes of string_ or unicode_.
See also
--------
add
- __rmod__(self, other)
- __rmul__(self, i)
- Return (self * i), that is string multiple concatenation,
element-wise.
See also
--------
multiply
- argsort(self, axis=-1, kind='quicksort', order=None)
- a.argsort(axis=-1, kind='quicksort', order=None)
Returns the indices that would sort this array.
Refer to `numpy.argsort` for full documentation.
See Also
--------
numpy.argsort : equivalent function
- capitalize(self)
- Return a copy of `self` with only the first character of each element
capitalized.
See also
--------
char.capitalize
- center(self, width, fillchar=' ')
- Return a copy of `self` with its elements centered in a
string of length `width`.
See also
--------
center
- count(self, sub, start=0, end=None)
- Returns an array with the number of non-overlapping occurrences of
substring `sub` in the range [`start`, `end`].
See also
--------
char.count
- decode(self, encoding=None, errors=None)
- Calls `str.decode` element-wise.
See also
--------
char.decode
- encode(self, encoding=None, errors=None)
- Calls `str.encode` element-wise.
See also
--------
char.encode
- endswith(self, suffix, start=0, end=None)
- Returns a boolean array which is `True` where the string element
in `self` ends with `suffix`, otherwise `False`.
See also
--------
char.endswith
- expandtabs(self, tabsize=8)
- Return a copy of each string element where all tab characters are
replaced by one or more spaces.
See also
--------
char.expandtabs
- find(self, sub, start=0, end=None)
- For each element, return the lowest index in the string where
substring `sub` is found.
See also
--------
char.find
- index(self, sub, start=0, end=None)
- Like `find`, but raises `ValueError` when the substring is not found.
See also
--------
char.index
- isalnum(self)
- Returns true for each element if all characters in the string
are alphanumeric and there is at least one character, false
otherwise.
See also
--------
char.isalnum
- isalpha(self)
- Returns true for each element if all characters in the string
are alphabetic and there is at least one character, false
otherwise.
See also
--------
char.isalpha
- isdecimal(self)
- For each element in `self`, return True if there are only
decimal characters in the element.
See also
--------
char.isdecimal
- isdigit(self)
- Returns true for each element if all characters in the string are
digits and there is at least one character, false otherwise.
See also
--------
char.isdigit
- islower(self)
- Returns true for each element if all cased characters in the
string are lowercase and there is at least one cased character,
false otherwise.
See also
--------
char.islower
- isnumeric(self)
- For each element in `self`, return True if there are only
numeric characters in the element.
See also
--------
char.isnumeric
- isspace(self)
- Returns true for each element if there are only whitespace
characters in the string and there is at least one character,
false otherwise.
See also
--------
char.isspace
- istitle(self)
- Returns true for each element if the element is a titlecased
string and there is at least one character, false otherwise.
See also
--------
char.istitle
- isupper(self)
- Returns true for each element if all cased characters in the
string are uppercase and there is at least one character, false
otherwise.
See also
--------
char.isupper
- join(self, seq)
- Return a string which is the concatenation of the strings in the
sequence `seq`.
See also
--------
char.join
- ljust(self, width, fillchar=' ')
- Return an array with the elements of `self` left-justified in a
string of length `width`.
See also
--------
char.ljust
- lower(self)
- Return an array with the elements of `self` converted to
lowercase.
See also
--------
char.lower
- lstrip(self, chars=None)
- For each element in `self`, return a copy with the leading characters
removed.
See also
--------
char.lstrip
- partition(self, sep)
- Partition each element in `self` around `sep`.
See also
--------
partition
- replace(self, old, new, count=None)
- For each element in `self`, return a copy of the string with all
occurrences of substring `old` replaced by `new`.
See also
--------
char.replace
- rfind(self, sub, start=0, end=None)
- For each element in `self`, return the highest index in the string
where substring `sub` is found, such that `sub` is contained
within [`start`, `end`].
See also
--------
char.rfind
- rindex(self, sub, start=0, end=None)
- Like `rfind`, but raises `ValueError` when the substring `sub` is
not found.
See also
--------
char.rindex
- rjust(self, width, fillchar=' ')
- Return an array with the elements of `self`
right-justified in a string of length `width`.
See also
--------
char.rjust
- rpartition(self, sep)
- Partition each element in `self` around `sep`.
See also
--------
rpartition
- rsplit(self, sep=None, maxsplit=None)
- For each element in `self`, return a list of the words in
the string, using `sep` as the delimiter string.
See also
--------
char.rsplit
- rstrip(self, chars=None)
- For each element in `self`, return a copy with the trailing
characters removed.
See also
--------
char.rstrip
- split(self, sep=None, maxsplit=None)
- For each element in `self`, return a list of the words in the
string, using `sep` as the delimiter string.
See also
--------
char.split
- splitlines(self, keepends=None)
- For each element in `self`, return a list of the lines in the
element, breaking at line boundaries.
See also
--------
char.splitlines
- startswith(self, prefix, start=0, end=None)
- Returns a boolean array which is `True` where the string element
in `self` starts with `prefix`, otherwise `False`.
See also
--------
char.startswith
- strip(self, chars=None)
- For each element in `self`, return a copy with the leading and
trailing characters removed.
See also
--------
char.strip
- swapcase(self)
- For each element in `self`, return a copy of the string with
uppercase characters converted to lowercase and vice versa.
See also
--------
char.swapcase
- title(self)
- For each element in `self`, return a titlecased version of the
string: words start with uppercase characters, all remaining cased
characters are lowercase.
See also
--------
char.title
- translate(self, table, deletechars=None)
- For each element in `self`, return a copy of the string where
all characters occurring in the optional argument
`deletechars` are removed, and the remaining characters have
been mapped through the given translation table.
See also
--------
char.translate
- upper(self)
- Return an array with the elements of `self` converted to
uppercase.
See also
--------
char.upper
- zfill(self, width)
- Return the numeric string left-filled with zeros in a string of
length `width`.
See also
--------
char.zfill
Static methods defined here:
- __new__(subtype, shape, itemsize=1, unicode=False, buffer=None, offset=0, strides=None, order='C')
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
Methods inherited from numpy.ndarray:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- a.__array__(|dtype) -> reference if type unchanged, copy otherwise.
Returns either a new reference to self if dtype is not given or a new array
of provided data type if dtype is different from the current dtype of the
array.
- __array_prepare__(...)
- a.__array_prepare__(obj) -> Object of same type as ndarray object obj.
- __array_wrap__(...)
- a.__array_wrap__(obj) -> Object of same type as ndarray object a.
- __contains__(...)
- x.__contains__(y) <==> y in x
- __copy__(...)
- a.__copy__([order])
Return a copy of the array.
Parameters
----------
order : {'C', 'F', 'A'}, optional
If order is 'C' (False) then the result is contiguous (default).
If order is 'Fortran' (True) then the result has fortran order.
If order is 'Any' (None) then the result has fortran order
only if the array already is in fortran order.
- __deepcopy__(...)
- a.__deepcopy__() -> Deep copy of array.
Used if copy.deepcopy is called on an array.
- __delitem__(...)
- x.__delitem__(y) <==> del x[y]
- __delslice__(...)
- x.__delslice__(i, j) <==> del x[i:j]
Use of negative indices is not supported.
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getslice__(...)
- x.__getslice__(i, j) <==> x[i:j]
Use of negative indices is not supported.
- __hex__(...)
- x.__hex__() <==> hex(x)
- __iadd__(...)
- x.__iadd__(y) <==> x+y
- __iand__(...)
- x.__iand__(y) <==> x&y
- __idiv__(...)
- x.__idiv__(y) <==> x/y
- __ifloordiv__(...)
- x.__ifloordiv__(y) <==> x//y
- __ilshift__(...)
- x.__ilshift__(y) <==> x<<y
- __imod__(...)
- x.__imod__(y) <==> x%y
- __imul__(...)
- x.__imul__(y) <==> x*y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __ior__(...)
- x.__ior__(y) <==> x|y
- __ipow__(...)
- x.__ipow__(y) <==> x**y
- __irshift__(...)
- x.__irshift__(y) <==> x>>y
- __isub__(...)
- x.__isub__(y) <==> x-y
- __iter__(...)
- x.__iter__() <==> iter(x)
- __itruediv__(...)
- x.__itruediv__(y) <==> x/y
- __ixor__(...)
- x.__ixor__(y) <==> x^y
- __len__(...)
- x.__len__() <==> len(x)
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- a.__reduce__()
For pickling.
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setitem__(...)
- x.__setitem__(i, y) <==> x[i]=y
- __setslice__(...)
- x.__setslice__(i, j, y) <==> x[i:j]=y
Use of negative indices is not supported.
- __setstate__(...)
- a.__setstate__(version, shape, dtype, isfortran, rawdata)
For unpickling.
Parameters
----------
version : int
optional pickle version. If omitted defaults to 0.
shape : tuple
dtype : data-type
isFortran : bool
rawdata : string or list
a binary string with the data (or a list if 'a' is an object array)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- a.all(axis=None, out=None)
Returns True if all elements evaluate to True.
Refer to `numpy.all` for full documentation.
See Also
--------
numpy.all : equivalent function
- any(...)
- a.any(axis=None, out=None)
Returns True if any of the elements of `a` evaluate to True.
Refer to `numpy.any` for full documentation.
See Also
--------
numpy.any : equivalent function
- argmax(...)
- a.argmax(axis=None, out=None)
Return indices of the maximum values along the given axis.
Refer to `numpy.argmax` for full documentation.
See Also
--------
numpy.argmax : equivalent function
- argmin(...)
- a.argmin(axis=None, out=None)
Return indices of the minimum values along the given axis of `a`.
Refer to `numpy.argmin` for detailed documentation.
See Also
--------
numpy.argmin : equivalent function
- astype(...)
- a.astype(t)
Copy of the array, cast to a specified type.
Parameters
----------
t : string or dtype
Typecode or data-type to which the array is cast.
Examples
--------
>>> x = np.array([1, 2, 2.5])
>>> x
array([ 1. , 2. , 2.5])
>>> x.astype(int)
array([1, 2, 2])
- byteswap(...)
- a.byteswap(inplace)
Swap the bytes of the array elements
Toggle between low-endian and big-endian data representation by
returning a byteswapped array, optionally swapped in-place.
Parameters
----------
inplace: bool, optional
If ``True``, swap bytes in-place, default is ``False``.
Returns
-------
out: ndarray
The byteswapped array. If `inplace` is ``True``, this is
a view to self.
Examples
--------
>>> A = np.array([1, 256, 8755], dtype=np.int16)
>>> map(hex, A)
['0x1', '0x100', '0x2233']
>>> A.byteswap(True)
array([ 256, 1, 13090], dtype=int16)
>>> map(hex, A)
['0x100', '0x1', '0x3322']
Arrays of strings are not swapped
>>> A = np.array(['ceg', 'fac'])
>>> A.byteswap()
array(['ceg', 'fac'],
dtype='|S3')
- choose(...)
- a.choose(choices, out=None, mode='raise')
Use an index array to construct a new array from a set of choices.
Refer to `numpy.choose` for full documentation.
See Also
--------
numpy.choose : equivalent function
- clip(...)
- a.clip(a_min, a_max, out=None)
Return an array whose values are limited to ``[a_min, a_max]``.
Refer to `numpy.clip` for full documentation.
See Also
--------
numpy.clip : equivalent function
- compress(...)
- a.compress(condition, axis=None, out=None)
Return selected slices of this array along given axis.
Refer to `numpy.compress` for full documentation.
See Also
--------
numpy.compress : equivalent function
- conj(...)
- a.conj()
Complex-conjugate all elements.
Refer to `numpy.conjugate` for full documentation.
See Also
--------
numpy.conjugate : equivalent function
- conjugate(...)
- a.conjugate()
Return the complex conjugate, element-wise.
Refer to `numpy.conjugate` for full documentation.
See Also
--------
numpy.conjugate : equivalent function
- copy(...)
- a.copy(order='C')
Return a copy of the array.
Parameters
----------
order : {'C', 'F', 'A'}, optional
By default, the result is stored in C-contiguous (row-major) order in
memory. If `order` is `F`, the result has 'Fortran' (column-major)
order. If order is 'A' ('Any'), then the result has the same order
as the input.
Examples
--------
>>> x = np.array([[1,2,3],[4,5,6]], order='F')
>>> y = x.copy()
>>> x.fill(0)
>>> x
array([[0, 0, 0],
[0, 0, 0]])
>>> y
array([[1, 2, 3],
[4, 5, 6]])
>>> y.flags['C_CONTIGUOUS']
True
- cumprod(...)
- a.cumprod(axis=None, dtype=None, out=None)
Return the cumulative product of the elements along the given axis.
Refer to `numpy.cumprod` for full documentation.
See Also
--------
numpy.cumprod : equivalent function
- cumsum(...)
- a.cumsum(axis=None, dtype=None, out=None)
Return the cumulative sum of the elements along the given axis.
Refer to `numpy.cumsum` for full documentation.
See Also
--------
numpy.cumsum : equivalent function
- diagonal(...)
- a.diagonal(offset=0, axis1=0, axis2=1)
Return specified diagonals.
Refer to `numpy.diagonal` for full documentation.
See Also
--------
numpy.diagonal : equivalent function
- dot(...)
- dump(...)
- a.dump(file)
Dump a pickle of the array to the specified file.
The array can be read back with pickle.load or numpy.load.
Parameters
----------
file : str
A string naming the dump file.
- dumps(...)
- a.dumps()
Returns the pickle of the array as a string.
pickle.loads or numpy.loads will convert the string back to an array.
Parameters
----------
None
- fill(...)
- a.fill(value)
Fill the array with a scalar value.
Parameters
----------
value : scalar
All elements of `a` will be assigned this value.
Examples
--------
>>> a = np.array([1, 2])
>>> a.fill(0)
>>> a
array([0, 0])
>>> a = np.empty(2)
>>> a.fill(1)
>>> a
array([ 1., 1.])
- flatten(...)
- a.flatten(order='C')
Return a copy of the array collapsed into one dimension.
Parameters
----------
order : {'C', 'F'}, optional
Whether to flatten in C (row-major) or Fortran (column-major) order.
The default is 'C'.
Returns
-------
y : ndarray
A copy of the input array, flattened to one dimension.
See Also
--------
ravel : Return a flattened array.
flat : A 1-D flat iterator over the array.
Examples
--------
>>> a = np.array([[1,2], [3,4]])
>>> a.flatten()
array([1, 2, 3, 4])
>>> a.flatten('F')
array([1, 3, 2, 4])
- getfield(...)
- a.getfield(dtype, offset)
Returns a field of the given array as a certain type.
A field is a view of the array data with each itemsize determined
by the given type and the offset into the current array, i.e. from
``offset * dtype.itemsize`` to ``(offset+1) * dtype.itemsize``.
Parameters
----------
dtype : str
String denoting the data type of the field.
offset : int
Number of `dtype.itemsize`'s to skip before beginning the element view.
Examples
--------
>>> x = np.diag([1.+1.j]*2)
>>> x
array([[ 1.+1.j, 0.+0.j],
[ 0.+0.j, 1.+1.j]])
>>> x.dtype
dtype('complex128')
>>> x.getfield('complex64', 0) # Note how this != x
array([[ 0.+1.875j, 0.+0.j ],
[ 0.+0.j , 0.+1.875j]], dtype=complex64)
>>> x.getfield('complex64',1) # Note how different this is than x
array([[ 0. +5.87173204e-39j, 0. +0.00000000e+00j],
[ 0. +0.00000000e+00j, 0. +5.87173204e-39j]], dtype=complex64)
>>> x.getfield('complex128', 0) # == x
array([[ 1.+1.j, 0.+0.j],
[ 0.+0.j, 1.+1.j]])
If the argument dtype is the same as x.dtype, then offset != 0 raises
a ValueError:
>>> x.getfield('complex128', 1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: Need 0 <= offset <= 0 for requested type but received offset = 1
>>> x.getfield('float64', 0)
array([[ 1., 0.],
[ 0., 1.]])
>>> x.getfield('float64', 1)
array([[ 1.77658241e-307, 0.00000000e+000],
[ 0.00000000e+000, 1.77658241e-307]])
- item(...)
- a.item(*args)
Copy an element of an array to a standard Python scalar and return it.
Parameters
----------
\*args : Arguments (variable number and type)
* none: in this case, the method only works for arrays
with one element (`a.size == 1`), which element is
copied into a standard Python scalar object and returned.
* int_type: this argument is interpreted as a flat index into
the array, specifying which element to copy and return.
* tuple of int_types: functions as does a single int_type argument,
except that the argument is interpreted as an nd-index into the
array.
Returns
-------
z : Standard Python scalar object
A copy of the specified element of the array as a suitable
Python scalar
Notes
-----
When the data type of `a` is longdouble or clongdouble, item() returns
a scalar array object because there is no available Python scalar that
would not lose information. Void arrays return a buffer object for item(),
unless fields are defined, in which case a tuple is returned.
`item` is very similar to a[args], except, instead of an array scalar,
a standard Python scalar is returned. This can be useful for speeding up
access to elements of the array and doing arithmetic on elements of the
array using Python's optimized math.
Examples
--------
>>> x = np.random.randint(9, size=(3, 3))
>>> x
array([[3, 1, 7],
[2, 8, 3],
[8, 5, 3]])
>>> x.item(3)
2
>>> x.item(7)
5
>>> x.item((0, 1))
1
>>> x.item((2, 2))
3
- itemset(...)
- a.itemset(*args)
Insert scalar into an array (scalar is cast to array's dtype, if possible)
There must be at least 1 argument, and define the last argument
as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster
than ``a[args] = item``. The item should be a scalar value and `args`
must select a single item in the array `a`.
Parameters
----------
\*args : Arguments
If one argument: a scalar, only used in case `a` is of size 1.
If two arguments: the last argument is the value to be set
and must be a scalar, the first argument specifies a single array
element location. It is either an int or a tuple.
Notes
-----
Compared to indexing syntax, `itemset` provides some speed increase
for placing a scalar into a particular location in an `ndarray`,
if you must do this. However, generally this is discouraged:
among other problems, it complicates the appearance of the code.
Also, when using `itemset` (and `item`) inside a loop, be sure
to assign the methods to a local variable to avoid the attribute
look-up at each loop iteration.
Examples
--------
>>> x = np.random.randint(9, size=(3, 3))
>>> x
array([[3, 1, 7],
[2, 8, 3],
[8, 5, 3]])
>>> x.itemset(4, 0)
>>> x.itemset((2, 2), 9)
>>> x
array([[3, 1, 7],
[2, 0, 3],
[8, 5, 9]])
- max(...)
- a.max(axis=None, out=None)
Return the maximum along a given axis.
Refer to `numpy.amax` for full documentation.
See Also
--------
numpy.amax : equivalent function
- mean(...)
- a.mean(axis=None, dtype=None, out=None)
Returns the average of the array elements along given axis.
Refer to `numpy.mean` for full documentation.
See Also
--------
numpy.mean : equivalent function
- min(...)
- a.min(axis=None, out=None)
Return the minimum along a given axis.
Refer to `numpy.amin` for full documentation.
See Also
--------
numpy.amin : equivalent function
- newbyteorder(...)
- arr.newbyteorder(new_order='S')
Return the array with the same data viewed with a different byte order.
Equivalent to::
arr.view(arr.dtype.newbytorder(new_order))
Changes are also made in all fields and sub-arrays of the array data
type.
Parameters
----------
new_order : string, optional
Byte order to force; a value from the byte order specifications
above. `new_order` codes can be any of::
* 'S' - swap dtype from current to opposite endian
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* {'|', 'I'} - ignore (no change to byte order)
The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_arr : array
New array object with the dtype reflecting given change to the
byte order.
- nonzero(...)
- a.nonzero()
Return the indices of the elements that are non-zero.
Refer to `numpy.nonzero` for full documentation.
See Also
--------
numpy.nonzero : equivalent function
- prod(...)
- a.prod(axis=None, dtype=None, out=None)
Return the product of the array elements over the given axis
Refer to `numpy.prod` for full documentation.
See Also
--------
numpy.prod : equivalent function
- ptp(...)
- a.ptp(axis=None, out=None)
Peak to peak (maximum - minimum) value along a given axis.
Refer to `numpy.ptp` for full documentation.
See Also
--------
numpy.ptp : equivalent function
- put(...)
- a.put(indices, values, mode='raise')
Set ``a.flat[n] = values[n]`` for all `n` in indices.
Refer to `numpy.put` for full documentation.
See Also
--------
numpy.put : equivalent function
- ravel(...)
- a.ravel([order])
Return a flattened array.
Refer to `numpy.ravel` for full documentation.
See Also
--------
numpy.ravel : equivalent function
ndarray.flat : a flat iterator on the array.
- repeat(...)
- a.repeat(repeats, axis=None)
Repeat elements of an array.
Refer to `numpy.repeat` for full documentation.
See Also
--------
numpy.repeat : equivalent function
- reshape(...)
- a.reshape(shape, order='C')
Returns an array containing the same data with a new shape.
Refer to `numpy.reshape` for full documentation.
See Also
--------
numpy.reshape : equivalent function
- resize(...)
- a.resize(new_shape, refcheck=True)
Change shape and size of array in-place.
Parameters
----------
new_shape : tuple of ints, or `n` ints
Shape of resized array.
refcheck : bool, optional
If False, reference count will not be checked. Default is True.
Returns
-------
None
Raises
------
ValueError
If `a` does not own its own data or references or views to it exist,
and the data memory must be changed.
SystemError
If the `order` keyword argument is specified. This behaviour is a
bug in NumPy.
See Also
--------
resize : Return a new array with the specified shape.
Notes
-----
This reallocates space for the data area if necessary.
Only contiguous arrays (data elements consecutive in memory) can be
resized.
The purpose of the reference count check is to make sure you
do not use this array as a buffer for another Python object and then
reallocate the memory. However, reference counts can increase in
other ways so if you are sure that you have not shared the memory
for this array with another Python object, then you may safely set
`refcheck` to False.
Examples
--------
Shrinking an array: array is flattened (in the order that the data are
stored in memory), resized, and reshaped:
>>> a = np.array([[0, 1], [2, 3]], order='C')
>>> a.resize((2, 1))
>>> a
array([[0],
[1]])
>>> a = np.array([[0, 1], [2, 3]], order='F')
>>> a.resize((2, 1))
>>> a
array([[0],
[2]])
Enlarging an array: as above, but missing entries are filled with zeros:
>>> b = np.array([[0, 1], [2, 3]])
>>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple
>>> b
array([[0, 1, 2],
[3, 0, 0]])
Referencing an array prevents resizing...
>>> c = a
>>> a.resize((1, 1))
Traceback (most recent call last):
...
ValueError: cannot resize an array that has been referenced ...
Unless `refcheck` is False:
>>> a.resize((1, 1), refcheck=False)
>>> a
array([[0]])
>>> c
array([[0]])
- round(...)
- a.round(decimals=0, out=None)
Return `a` with each element rounded to the given number of decimals.
Refer to `numpy.around` for full documentation.
See Also
--------
numpy.around : equivalent function
- searchsorted(...)
- a.searchsorted(v, side='left')
Find indices where elements of v should be inserted in a to maintain order.
For full documentation, see `numpy.searchsorted`
See Also
--------
numpy.searchsorted : equivalent function
- setfield(...)
- a.setfield(val, dtype, offset=0)
Put a value into a specified place in a field defined by a data-type.
Place `val` into `a`'s field defined by `dtype` and beginning `offset`
bytes into the field.
Parameters
----------
val : object
Value to be placed in field.
dtype : dtype object
Data-type of the field in which to place `val`.
offset : int, optional
The number of bytes into the field at which to place `val`.
Returns
-------
None
See Also
--------
getfield
Examples
--------
>>> x = np.eye(3)
>>> x.getfield(np.float64)
array([[ 1., 0., 0.],
[ 0., 1., 0.],
[ 0., 0., 1.]])
>>> x.setfield(3, np.int32)
>>> x.getfield(np.int32)
array([[3, 3, 3],
[3, 3, 3],
[3, 3, 3]])
>>> x
array([[ 1.00000000e+000, 1.48219694e-323, 1.48219694e-323],
[ 1.48219694e-323, 1.00000000e+000, 1.48219694e-323],
[ 1.48219694e-323, 1.48219694e-323, 1.00000000e+000]])
>>> x.setfield(np.eye(3), np.int32)
>>> x
array([[ 1., 0., 0.],
[ 0., 1., 0.],
[ 0., 0., 1.]])
- setflags(...)
- a.setflags(write=None, align=None, uic=None)
Set array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.
These Boolean-valued flags affect how numpy interprets the memory
area used by `a` (see Notes below). The ALIGNED flag can only
be set to True if the data is actually aligned according to the type.
The UPDATEIFCOPY flag can never be set to True. The flag WRITEABLE
can only be set to True if the array owns its own memory, or the
ultimate owner of the memory exposes a writeable buffer interface,
or is a string. (The exception for string is made so that unpickling
can be done without copying memory.)
Parameters
----------
write : bool, optional
Describes whether or not `a` can be written to.
align : bool, optional
Describes whether or not `a` is aligned properly for its type.
uic : bool, optional
Describes whether or not `a` is a copy of another "base" array.
Notes
-----
Array flags provide information about how the memory area used
for the array is to be interpreted. There are 6 Boolean flags
in use, only three of which can be changed by the user:
UPDATEIFCOPY, WRITEABLE, and ALIGNED.
WRITEABLE (W) the data area can be written to;
ALIGNED (A) the data and strides are aligned appropriately for the hardware
(as determined by the compiler);
UPDATEIFCOPY (U) this array is a copy of some other array (referenced
by .base). When this array is deallocated, the base array will be
updated with the contents of this array.
All flags can be accessed using their first (upper case) letter as well
as the full name.
Examples
--------
>>> y
array([[3, 1, 7],
[2, 0, 0],
[8, 5, 9]])
>>> y.flags
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
>>> y.setflags(write=0, align=0)
>>> y.flags
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : False
ALIGNED : False
UPDATEIFCOPY : False
>>> y.setflags(uic=1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: cannot set UPDATEIFCOPY flag to True
- sort(...)
- a.sort(axis=-1, kind='quicksort', order=None)
Sort an array, in-place.
Parameters
----------
axis : int, optional
Axis along which to sort. Default is -1, which means sort along the
last axis.
kind : {'quicksort', 'mergesort', 'heapsort'}, optional
Sorting algorithm. Default is 'quicksort'.
order : list, optional
When `a` is an array with fields defined, this argument specifies
which fields to compare first, second, etc. Not all fields need be
specified.
See Also
--------
numpy.sort : Return a sorted copy of an array.
argsort : Indirect sort.
lexsort : Indirect stable sort on multiple keys.
searchsorted : Find elements in sorted array.
Notes
-----
See ``sort`` for notes on the different sorting algorithms.
Examples
--------
>>> a = np.array([[1,4], [3,1]])
>>> a.sort(axis=1)
>>> a
array([[1, 4],
[1, 3]])
>>> a.sort(axis=0)
>>> a
array([[1, 3],
[1, 4]])
Use the `order` keyword to specify a field to use when sorting a
structured array:
>>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])
>>> a.sort(order='y')
>>> a
array([('c', 1), ('a', 2)],
dtype=[('x', '|S1'), ('y', '<i4')])
- squeeze(...)
- a.squeeze()
Remove single-dimensional entries from the shape of `a`.
Refer to `numpy.squeeze` for full documentation.
See Also
--------
numpy.squeeze : equivalent function
- std(...)
- a.std(axis=None, dtype=None, out=None, ddof=0)
Returns the standard deviation of the array elements along given axis.
Refer to `numpy.std` for full documentation.
See Also
--------
numpy.std : equivalent function
- sum(...)
- a.sum(axis=None, dtype=None, out=None)
Return the sum of the array elements over the given axis.
Refer to `numpy.sum` for full documentation.
See Also
--------
numpy.sum : equivalent function
- swapaxes(...)
- a.swapaxes(axis1, axis2)
Return a view of the array with `axis1` and `axis2` interchanged.
Refer to `numpy.swapaxes` for full documentation.
See Also
--------
numpy.swapaxes : equivalent function
- take(...)
- a.take(indices, axis=None, out=None, mode='raise')
Return an array formed from the elements of `a` at the given indices.
Refer to `numpy.take` for full documentation.
See Also
--------
numpy.take : equivalent function
- tofile(...)
- a.tofile(fid, sep="", format="%s")
Write array to a file as text or binary (default).
Data is always written in 'C' order, independent of the order of `a`.
The data produced by this method can be recovered using the function
fromfile().
Parameters
----------
fid : file or str
An open file object, or a string containing a filename.
sep : str
Separator between array items for text output.
If "" (empty), a binary file is written, equivalent to
``file.write(a.tostring())``.
format : str
Format string for text file output.
Each entry in the array is formatted to text by first converting
it to the closest Python type, and then using "format" % item.
Notes
-----
This is a convenience function for quick storage of array data.
Information on endianness and precision is lost, so this method is not a
good choice for files intended to archive data or transport data between
machines with different endianness. Some of these problems can be overcome
by outputting the data as text files, at the expense of speed and file
size.
- tolist(...)
- a.tolist()
Return the array as a (possibly nested) list.
Return a copy of the array data as a (nested) Python list.
Data items are converted to the nearest compatible Python type.
Parameters
----------
none
Returns
-------
y : list
The possibly nested list of array elements.
Notes
-----
The array may be recreated, ``a = np.array(a.tolist())``.
Examples
--------
>>> a = np.array([1, 2])
>>> a.tolist()
[1, 2]
>>> a = np.array([[1, 2], [3, 4]])
>>> list(a)
[array([1, 2]), array([3, 4])]
>>> a.tolist()
[[1, 2], [3, 4]]
- tostring(...)
- a.tostring(order='C')
Construct a Python string containing the raw data bytes in the array.
Constructs a Python string showing a copy of the raw contents of
data memory. The string can be produced in either 'C' or 'Fortran',
or 'Any' order (the default is 'C'-order). 'Any' order means C-order
unless the F_CONTIGUOUS flag in the array is set, in which case it
means 'Fortran' order.
Parameters
----------
order : {'C', 'F', None}, optional
Order of the data for multidimensional arrays:
C, Fortran, or the same as for the original array.
Returns
-------
s : str
A Python string exhibiting a copy of `a`'s raw data.
Examples
--------
>>> x = np.array([[0, 1], [2, 3]])
>>> x.tostring()
'\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00'
>>> x.tostring('C') == x.tostring()
True
>>> x.tostring('F')
'\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x03\x00\x00\x00'
- trace(...)
- a.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)
Return the sum along diagonals of the array.
Refer to `numpy.trace` for full documentation.
See Also
--------
numpy.trace : equivalent function
- transpose(...)
- a.transpose(*axes)
Returns a view of the array with axes transposed.
For a 1-D array, this has no effect. (To change between column and
row vectors, first cast the 1-D array into a matrix object.)
For a 2-D array, this is the usual matrix transpose.
For an n-D array, if axes are given, their order indicates how the
axes are permuted (see Examples). If axes are not provided and
``a.shape = (i[0], i[1], ... i[n-2], i[n-1])``, then
``a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])``.
Parameters
----------
axes : None, tuple of ints, or `n` ints
* None or no argument: reverses the order of the axes.
* tuple of ints: `i` in the `j`-th place in the tuple means `a`'s
`i`-th axis becomes `a.transpose()`'s `j`-th axis.
* `n` ints: same as an n-tuple of the same ints (this form is
intended simply as a "convenience" alternative to the tuple form)
Returns
-------
out : ndarray
View of `a`, with axes suitably permuted.
See Also
--------
ndarray.T : Array property returning the array transposed.
Examples
--------
>>> a = np.array([[1, 2], [3, 4]])
>>> a
array([[1, 2],
[3, 4]])
>>> a.transpose()
array([[1, 3],
[2, 4]])
>>> a.transpose((1, 0))
array([[1, 3],
[2, 4]])
>>> a.transpose(1, 0)
array([[1, 3],
[2, 4]])
- var(...)
- a.var(axis=None, dtype=None, out=None, ddof=0)
Returns the variance of the array elements, along given axis.
Refer to `numpy.var` for full documentation.
See Also
--------
numpy.var : equivalent function
- view(...)
- a.view(dtype=None, type=None)
New view of array with the same data.
Parameters
----------
dtype : data-type, optional
Data-type descriptor of the returned view, e.g., float32 or int16.
The default, None, results in the view having the same data-type
as `a`.
type : Python type, optional
Type of the returned view, e.g., ndarray or matrix. Again, the
default None results in type preservation.
Notes
-----
``a.view()`` is used two different ways:
``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view
of the array's memory with a different data-type. This can cause a
reinterpretation of the bytes of memory.
``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just
returns an instance of `ndarray_subclass` that looks at the same array
(same shape, dtype, etc.) This does not cause a reinterpretation of the
memory.
Examples
--------
>>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])
Viewing array data using a different type and dtype:
>>> y = x.view(dtype=np.int16, type=np.matrix)
>>> y
matrix([[513]], dtype=int16)
>>> print type(y)
<class 'numpy.matrixlib.defmatrix.matrix'>
Creating a view on a structured array so it can be used in calculations
>>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)])
>>> xv = x.view(dtype=np.int8).reshape(-1,2)
>>> xv
array([[1, 2],
[3, 4]], dtype=int8)
>>> xv.mean(0)
array([ 2., 3.])
Making changes to the view changes the underlying array
>>> xv[0,1] = 20
>>> print x
[(1, 20) (3, 4)]
Using a view to convert an array to a record array:
>>> z = x.view(np.recarray)
>>> z.a
array([1], dtype=int8)
Views share data:
>>> x[0] = (9, 10)
>>> z[0]
(9, 10)
Data descriptors inherited from numpy.ndarray:
- T
- Same as transpose(), except that self is returned if
self.ndim < 2.
Examples
--------
>>> x = np.array([[1.,2.],[3.,4.]])
>>> x
array([[ 1., 2.],
[ 3., 4.]])
>>> x.T
array([[ 1., 3.],
[ 2., 4.]])
>>> x = np.array([1.,2.,3.,4.])
>>> x
array([ 1., 2., 3., 4.])
>>> x.T
array([ 1., 2., 3., 4.])
- __array_interface__
- Array protocol: Python side.
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: C-struct side.
- base
- Base object if memory is from some other object.
Examples
--------
The base of an array that owns its memory is None:
>>> x = np.array([1,2,3,4])
>>> x.base is None
True
Slicing creates a view, whose memory is shared with x:
>>> y = x[2:]
>>> y.base is x
True
- ctypes
- An object to simplify the interaction of the array with the ctypes
module.
This attribute creates an object that makes it easier to use arrays
when calling shared libraries with the ctypes module. The returned
object has, among others, data, shape, and strides attributes (see
Notes below) which themselves return ctypes objects that can be used
as arguments to a shared library.
Parameters
----------
None
Returns
-------
c : Python object
Possessing attributes data, shape, strides, etc.
See Also
--------
numpy.ctypeslib
Notes
-----
Below are the public attributes of this object which were documented
in "Guide to NumPy" (we have omitted undocumented public attributes,
as well as documented private attributes):
* data: A pointer to the memory area of the array as a Python integer.
This memory area may contain data that is not aligned, or not in correct
byte-order. The memory area may not even be writeable. The array
flags and data-type of this array should be respected when passing this
attribute to arbitrary C-code to avoid trouble that can include Python
crashing. User Beware! The value of this attribute is exactly the same
as self._array_interface_['data'][0].
* shape (c_intp*self.ndim): A ctypes array of length self.ndim where
the basetype is the C-integer corresponding to dtype('p') on this
platform. This base-type could be c_int, c_long, or c_longlong
depending on the platform. The c_intp type is defined accordingly in
numpy.ctypeslib. The ctypes array contains the shape of the underlying
array.
* strides (c_intp*self.ndim): A ctypes array of length self.ndim where
the basetype is the same as for the shape attribute. This ctypes array
contains the strides information from the underlying array. This strides
information is important for showing how many bytes must be jumped to
get to the next element in the array.
* data_as(obj): Return the data pointer cast to a particular c-types object.
For example, calling self._as_parameter_ is equivalent to
data_as(ctypes.c_void_p). Perhaps you want to use the data as a
pointer to a ctypes array of floating-point data:
data_as(ctypes.POINTER(ctypes.c_double)).
* shape_as(obj): Return the shape tuple as an array of some other c-types
type. For example: shape_as(ctypes.c_short).
* strides_as(obj): Return the strides tuple as an array of some other
c-types type. For example: strides_as(ctypes.c_longlong).
Be careful using the ctypes attribute - especially on temporary
arrays or arrays constructed on the fly. For example, calling
``(a+b).ctypes.data_as(ctypes.c_void_p)`` returns a pointer to memory
that is invalid because the array created as (a+b) is deallocated
before the next Python statement. You can avoid this problem using
either ``c=a+b`` or ``ct=(a+b).ctypes``. In the latter case, ct will
hold a reference to the array until ct is deleted or re-assigned.
If the ctypes module is not available, then the ctypes attribute
of array objects still returns something useful, but ctypes objects
are not returned and errors may be raised instead. In particular,
the object will still have the as parameter attribute which will
return an integer equal to the data attribute.
Examples
--------
>>> import ctypes
>>> x
array([[0, 1],
[2, 3]])
>>> x.ctypes.data
30439712
>>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_long))
<ctypes.LP_c_long object at 0x01F01300>
>>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_long)).contents
c_long(0)
>>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_longlong)).contents
c_longlong(4294967296L)
>>> x.ctypes.shape
<numpy.core._internal.c_long_Array_2 object at 0x01FFD580>
>>> x.ctypes.shape_as(ctypes.c_long)
<numpy.core._internal.c_long_Array_2 object at 0x01FCE620>
>>> x.ctypes.strides
<numpy.core._internal.c_long_Array_2 object at 0x01FCE620>
>>> x.ctypes.strides_as(ctypes.c_longlong)
<numpy.core._internal.c_longlong_Array_2 object at 0x01F01300>
- data
- Python buffer object pointing to the start of the array's data.
- dtype
- Data-type of the array's elements.
Parameters
----------
None
Returns
-------
d : numpy dtype object
See Also
--------
numpy.dtype
Examples
--------
>>> x
array([[0, 1],
[2, 3]])
>>> x.dtype
dtype('int32')
>>> type(x.dtype)
<type 'numpy.dtype'>
- flags
- Information about the memory layout of the array.
Attributes
----------
C_CONTIGUOUS (C)
The data is in a single, C-style contiguous segment.
F_CONTIGUOUS (F)
The data is in a single, Fortran-style contiguous segment.
OWNDATA (O)
The array owns the memory it uses or borrows it from another object.
WRITEABLE (W)
The data area can be written to. Setting this to False locks
the data, making it read-only. A view (slice, etc.) inherits WRITEABLE
from its base array at creation time, but a view of a writeable
array may be subsequently locked while the base array remains writeable.
(The opposite is not true, in that a view of a locked array may not
be made writeable. However, currently, locking a base object does not
lock any views that already reference it, so under that circumstance it
is possible to alter the contents of a locked array via a previously
created writeable view onto it.) Attempting to change a non-writeable
array raises a RuntimeError exception.
ALIGNED (A)
The data and strides are aligned appropriately for the hardware.
UPDATEIFCOPY (U)
This array is a copy of some other array. When this array is
deallocated, the base array will be updated with the contents of
this array.
FNC
F_CONTIGUOUS and not C_CONTIGUOUS.
FORC
F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).
BEHAVED (B)
ALIGNED and WRITEABLE.
CARRAY (CA)
BEHAVED and C_CONTIGUOUS.
FARRAY (FA)
BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.
Notes
-----
The `flags` object can be accessed dictionary-like (as in ``a.flags['WRITEABLE']``),
or by using lowercased attribute names (as in ``a.flags.writeable``). Short flag
names are only supported in dictionary access.
Only the UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be changed by
the user, via direct assignment to the attribute or dictionary entry,
or by calling `ndarray.setflags`.
The array flags cannot be set arbitrarily:
- UPDATEIFCOPY can only be set ``False``.
- ALIGNED can only be set ``True`` if the data is truly aligned.
- WRITEABLE can only be set ``True`` if the array owns its own memory
or the ultimate owner of the memory exposes a writeable buffer
interface or is a string.
- flat
- A 1-D iterator over the array.
This is a `numpy.flatiter` instance, which acts similarly to, but is not
a subclass of, Python's built-in iterator object.
See Also
--------
flatten : Return a copy of the array collapsed into one dimension.
flatiter
Examples
--------
>>> x = np.arange(1, 7).reshape(2, 3)
>>> x
array([[1, 2, 3],
[4, 5, 6]])
>>> x.flat[3]
4
>>> x.T
array([[1, 4],
[2, 5],
[3, 6]])
>>> x.T.flat[3]
5
>>> type(x.flat)
<type 'numpy.flatiter'>
An assignment example:
>>> x.flat = 3; x
array([[3, 3, 3],
[3, 3, 3]])
>>> x.flat[[1,4]] = 1; x
array([[3, 1, 3],
[3, 1, 3]])
- imag
- The imaginary part of the array.
Examples
--------
>>> x = np.sqrt([1+0j, 0+1j])
>>> x.imag
array([ 0. , 0.70710678])
>>> x.imag.dtype
dtype('float64')
- itemsize
- Length of one array element in bytes.
Examples
--------
>>> x = np.array([1,2,3], dtype=np.float64)
>>> x.itemsize
8
>>> x = np.array([1,2,3], dtype=np.complex128)
>>> x.itemsize
16
- nbytes
- Total bytes consumed by the elements of the array.
Notes
-----
Does not include memory consumed by non-element attributes of the
array object.
Examples
--------
>>> x = np.zeros((3,5,2), dtype=np.complex128)
>>> x.nbytes
480
>>> np.prod(x.shape) * x.itemsize
480
- ndim
- Number of array dimensions.
Examples
--------
>>> x = np.array([1, 2, 3])
>>> x.ndim
1
>>> y = np.zeros((2, 3, 4))
>>> y.ndim
3
- real
- The real part of the array.
Examples
--------
>>> x = np.sqrt([1+0j, 0+1j])
>>> x.real
array([ 1. , 0.70710678])
>>> x.real.dtype
dtype('float64')
See Also
--------
numpy.real : equivalent function
- shape
- Tuple of array dimensions.
Notes
-----
May be used to "reshape" the array, as long as this would not
require a change in the total number of elements
Examples
--------
>>> x = np.array([1, 2, 3, 4])
>>> x.shape
(4,)
>>> y = np.zeros((2, 3, 4))
>>> y.shape
(2, 3, 4)
>>> y.shape = (3, 8)
>>> y
array([[ 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0.]])
>>> y.shape = (3, 6)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: total size of new array must be unchanged
- size
- Number of elements in the array.
Equivalent to ``np.prod(a.shape)``, i.e., the product of the array's
dimensions.
Examples
--------
>>> x = np.zeros((3, 5, 2), dtype=np.complex128)
>>> x.size
30
>>> np.prod(x.shape)
30
- strides
- Tuple of bytes to step in each dimension when traversing an array.
The byte offset of element ``(i[0], i[1], ..., i[n])`` in an array `a`
is::
offset = sum(np.array(i) * a.strides)
A more detailed explanation of strides can be found in the
"ndarray.rst" file in the NumPy reference guide.
Notes
-----
Imagine an array of 32-bit integers (each 4 bytes)::
x = np.array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]], dtype=np.int32)
This array is stored in memory as 40 bytes, one after the other
(known as a contiguous block of memory). The strides of an array tell
us how many bytes we have to skip in memory to move to the next position
along a certain axis. For example, we have to skip 4 bytes (1 value) to
move to the next column, but 20 bytes (5 values) to get to the same
position in the next row. As such, the strides for the array `x` will be
``(20, 4)``.
See Also
--------
numpy.lib.stride_tricks.as_strided
Examples
--------
>>> y = np.reshape(np.arange(2*3*4), (2,3,4))
>>> y
array([[[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]],
[[12, 13, 14, 15],
[16, 17, 18, 19],
[20, 21, 22, 23]]])
>>> y.strides
(48, 16, 4)
>>> y[1,1,1]
17
>>> offset=sum(y.strides * np.array((1,1,1)))
>>> offset/y.itemsize
17
>>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0)
>>> x.strides
(32, 4, 224, 1344)
>>> i = np.array([3,5,2,2])
>>> offset = sum(i * x.strides)
>>> x[3,5,2,2]
813
>>> offset / x.itemsize
813
|
clongdouble = class complex256(complexfloating) |
| |
Composed of two 128 bit floats
|
| |
- Method resolution order:
- complex256
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __complex__(...)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
clongfloat = class complex256(complexfloating) |
| |
Composed of two 128 bit floats
|
| |
- Method resolution order:
- complex256
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __complex__(...)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class complex128(complexfloating, __builtin__.complex) |
| |
Composed of two 64 bit floats
|
| |
- Method resolution order:
- complex128
- complexfloating
- inexact
- number
- generic
- __builtin__.complex
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.complex:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- complex.__format__() -> str
Converts to a string according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
|
class complex256(complexfloating) |
| |
Composed of two 128 bit floats
|
| |
- Method resolution order:
- complex256
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __complex__(...)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class complex64(complexfloating) |
| |
Composed of two 32 bit floats
|
| |
- Method resolution order:
- complex64
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __complex__(...)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
complex_ = class complex128(complexfloating, __builtin__.complex) |
| |
Composed of two 64 bit floats
|
| |
- Method resolution order:
- complex128
- complexfloating
- inexact
- number
- generic
- __builtin__.complex
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.complex:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- complex.__format__() -> str
Converts to a string according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
|
class complexfloating(inexact) |
| | |
- Method resolution order:
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
csingle = class complex64(complexfloating) |
| |
Composed of two 32 bit floats
|
| |
- Method resolution order:
- complex64
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __complex__(...)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
double = class float64(floating, __builtin__.float) |
| |
64-bit floating-point number. Character code 'd'. Python float compatible.
|
| |
- Method resolution order:
- float64
- floating
- inexact
- number
- generic
- __builtin__.float
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.float:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- float.__format__(format_spec) -> string
Formats the float according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Returns the Integral closest to x between 0 and x.
- as_integer_ratio(...)
- float.as_integer_ratio() -> (int, int)
Returns a pair of integers, whose ratio is exactly equal to the original
float and with a positive denominator.
Raises OverflowError on infinities and a ValueError on NaNs.
>>> (10.0).as_integer_ratio()
(10, 1)
>>> (0.0).as_integer_ratio()
(0, 1)
>>> (-.25).as_integer_ratio()
(-1, 4)
- hex(...)
- float.hex() -> string
Return a hexadecimal representation of a floating-point number.
>>> (-0.1).hex()
'-0x1.999999999999ap-4'
>>> 3.14159.hex()
'0x1.921f9f01b866ep+1'
- is_integer(...)
- Returns True if the float is an integer.
Data and other attributes inherited from __builtin__.float:
- __getformat__ = <built-in method __getformat__ of type object>
- float.__getformat__(typestr) -> string
You probably don't want to use this function. It exists mainly to be
used in Python's test suite.
typestr must be 'double' or 'float'. This function returns whichever of
'unknown', 'IEEE, big-endian' or 'IEEE, little-endian' best describes the
format of floating point numbers used by the C type named by typestr.
- __setformat__ = <built-in method __setformat__ of type object>
- float.__setformat__(typestr, fmt) -> None
You probably don't want to use this function. It exists mainly to be
used in Python's test suite.
typestr must be 'double' or 'float'. fmt must be one of 'unknown',
'IEEE, big-endian' or 'IEEE, little-endian', and in addition can only be
one of the latter two if it appears to match the underlying C reality.
Overrides the automatic determination of C-level floating point type.
This affects how floats are converted to and from binary strings.
- fromhex = <built-in method fromhex of type object>
- float.fromhex(string) -> float
Create a floating-point number from a hexadecimal string.
>>> float.fromhex('0x1.ffffp10')
2047.984375
>>> float.fromhex('-0x1p-1074')
-4.9406564584124654e-324
|
class dtype(__builtin__.object) |
| |
dtype(obj, align=False, copy=False)
Create a data type object.
A numpy array is homogeneous, and contains elements described by a
dtype object. A dtype object can be constructed from different
combinations of fundamental numeric types.
Parameters
----------
obj
Object to be converted to a data type object.
align : bool, optional
Add padding to the fields to match what a C compiler would output
for a similar C-struct. Can be ``True`` only if `obj` is a dictionary
or a comma-separated string.
copy : bool, optional
Make a new copy of the data-type object. If ``False``, the result
may just be a reference to a built-in data-type object.
Examples
--------
Using array-scalar type:
>>> np.dtype(np.int16)
dtype('int16')
Record, one field name 'f1', containing int16:
>>> np.dtype([('f1', np.int16)])
dtype([('f1', '<i2')])
Record, one field named 'f1', in itself containing a record with one field:
>>> np.dtype([('f1', [('f1', np.int16)])])
dtype([('f1', [('f1', '<i2')])])
Record, two fields: the first field contains an unsigned int, the
second an int32:
>>> np.dtype([('f1', np.uint), ('f2', np.int32)])
dtype([('f1', '<u4'), ('f2', '<i4')])
Using array-protocol type strings:
>>> np.dtype([('a','f8'),('b','S10')])
dtype([('a', '<f8'), ('b', '|S10')])
Using comma-separated field formats. The shape is (2,3):
>>> np.dtype("i4, (2,3)f8")
dtype([('f0', '<i4'), ('f1', '<f8', (2, 3))])
Using tuples. ``int`` is a fixed type, 3 the field's shape. ``void``
is a flexible type, here of size 10:
>>> np.dtype([('hello',(np.int,3)),('world',np.void,10)])
dtype([('hello', '<i4', 3), ('world', '|V10')])
Subdivide ``int16`` into 2 ``int8``'s, called x and y. 0 and 1 are
the offsets in bytes:
>>> np.dtype((np.int16, {'x':(np.int8,0), 'y':(np.int8,1)}))
dtype(('<i2', [('x', '|i1'), ('y', '|i1')]))
Using dictionaries. Two fields named 'gender' and 'age':
>>> np.dtype({'names':['gender','age'], 'formats':['S1',np.uint8]})
dtype([('gender', '|S1'), ('age', '|u1')])
Offsets in bytes, here 0 and 25:
>>> np.dtype({'surname':('S25',0),'age':(np.uint8,25)})
dtype([('surname', '|S25'), ('age', '|u1')])
|
| |
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __len__(...)
- x.__len__() <==> len(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mul__(...)
- x.__mul__(n) <==> x*n
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rmul__(...)
- x.__rmul__(n) <==> n*x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new dtype with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
Parameters
----------
new_order : string, optional
Byte order to force; a value from the byte order
specifications below. The default value ('S') results in
swapping the current byte order.
`new_order` codes can be any of::
* 'S' - swap dtype from current to opposite endian
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* {'|', 'I'} - ignore (no change to byte order)
The code does a case-insensitive check on the first letter of
`new_order` for these alternatives. For example, any of '>'
or 'B' or 'b' or 'brian' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New dtype object with the given change to the byte order.
Notes
-----
Changes are also made in all fields and sub-arrays of the data type.
Examples
--------
>>> import sys
>>> sys_is_le = sys.byteorder == 'little'
>>> native_code = sys_is_le and '<' or '>'
>>> swapped_code = sys_is_le and '>' or '<'
>>> native_dt = np.dtype(native_code+'i2')
>>> swapped_dt = np.dtype(swapped_code+'i2')
>>> native_dt.newbyteorder('S') == swapped_dt
True
>>> native_dt.newbyteorder() == swapped_dt
True
>>> native_dt == swapped_dt.newbyteorder('S')
True
>>> native_dt == swapped_dt.newbyteorder('=')
True
>>> native_dt == swapped_dt.newbyteorder('N')
True
>>> native_dt == native_dt.newbyteorder('|')
True
>>> np.dtype('<i2') == native_dt.newbyteorder('<')
True
>>> np.dtype('<i2') == native_dt.newbyteorder('L')
True
>>> np.dtype('>i2') == native_dt.newbyteorder('>')
True
>>> np.dtype('>i2') == native_dt.newbyteorder('B')
True
Data descriptors defined here:
- alignment
- The required alignment (bytes) of this data-type according to the compiler.
More information is available in the C-API section of the manual.
- base
- byteorder
- A character indicating the byte-order of this data-type object.
One of:
=== ==============
'=' native
'<' little-endian
'>' big-endian
'|' not applicable
=== ==============
All built-in data-type objects have byteorder either '=' or '|'.
Examples
--------
>>> dt = np.dtype('i2')
>>> dt.byteorder
'='
>>> # endian is not relevant for 8 bit numbers
>>> np.dtype('i1').byteorder
'|'
>>> # or ASCII strings
>>> np.dtype('S2').byteorder
'|'
>>> # Even if specific code is given, and it is native
>>> # '=' is the byteorder
>>> import sys
>>> sys_is_le = sys.byteorder == 'little'
>>> native_code = sys_is_le and '<' or '>'
>>> swapped_code = sys_is_le and '>' or '<'
>>> dt = np.dtype(native_code + 'i2')
>>> dt.byteorder
'='
>>> # Swapped code shows up as itself
>>> dt = np.dtype(swapped_code + 'i2')
>>> dt.byteorder == swapped_code
True
- char
- A unique character code for each of the 21 different built-in types.
- descr
- Array-interface compliant full description of the data-type.
The format is that required by the 'descr' key in the
`__array_interface__` attribute.
- fields
- Dictionary of named fields defined for this data type, or ``None``.
The dictionary is indexed by keys that are the names of the fields.
Each entry in the dictionary is a tuple fully describing the field::
(dtype, offset[, title])
If present, the optional title can be any object (if it is a string
or unicode then it will also be a key in the fields dictionary,
otherwise it's meta-data). Notice also that the first two elements
of the tuple can be passed directly as arguments to the ``ndarray.getfield``
and ``ndarray.setfield`` methods.
See Also
--------
ndarray.getfield, ndarray.setfield
Examples
--------
>>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])
>>> print dt.fields
{'grades': (dtype(('float64',(2,))), 16), 'name': (dtype('|S16'), 0)}
- flags
- Bit-flags describing how this data type is to be interpreted.
Bit-masks are in `numpy.core.multiarray` as the constants
`ITEM_HASOBJECT`, `LIST_PICKLE`, `ITEM_IS_POINTER`, `NEEDS_INIT`,
`NEEDS_PYAPI`, `USE_GETITEM`, `USE_SETITEM`. A full explanation
of these flags is in C-API documentation; they are largely useful
for user-defined data-types.
- hasobject
- Boolean indicating whether this dtype contains any reference-counted
objects in any fields or sub-dtypes.
Recall that what is actually in the ndarray memory representing
the Python object is the memory address of that object (a pointer).
Special handling may be required, and this attribute is useful for
distinguishing data types that may contain arbitrary Python objects
and data-types that won't.
- isbuiltin
- Integer indicating how this dtype relates to the built-in dtypes.
Read-only.
= ========================================================================
0 if this is a structured array type, with fields
1 if this is a dtype compiled into numpy (such as ints, floats etc)
2 if the dtype is for a user-defined numpy type
A user-defined type uses the numpy C-API machinery to extend
numpy to handle a new array type. See
:ref:`user.user-defined-data-types` in the Numpy manual.
= ========================================================================
Examples
--------
>>> dt = np.dtype('i2')
>>> dt.isbuiltin
1
>>> dt = np.dtype('f8')
>>> dt.isbuiltin
1
>>> dt = np.dtype([('field1', 'f8')])
>>> dt.isbuiltin
0
- isnative
- Boolean indicating whether the byte order of this dtype is native
to the platform.
- itemsize
- The element size of this data-type object.
For 18 of the 21 types this number is fixed by the data-type.
For the flexible data-types, this number can be anything.
- kind
- A character code (one of 'biufcSUV') identifying the general kind of data.
- metadata
- name
- A bit-width name for this data-type.
Un-sized flexible data-type objects do not have this attribute.
- names
- Ordered list of field names, or ``None`` if there are no fields.
The names are ordered according to increasing byte offset. This can be
used, for example, to walk through all of the named fields in offset order.
Examples
--------
>>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])
>>> dt.names
('name', 'grades')
- num
- A unique number for each of the 21 different built-in types.
These are roughly ordered from least-to-most precision.
- shape
- Shape tuple of the sub-array if this data type describes a sub-array,
and ``()`` otherwise.
- str
- The array-protocol typestring of this data-type object.
- subdtype
- Tuple ``(item_dtype, shape)`` if this `dtype` describes a sub-array, and
None otherwise.
The *shape* is the fixed shape of the sub-array described by this
data type, and *item_dtype* the data type of the array.
If a field whose dtype object has this attribute is retrieved,
then the extra dimensions implied by *shape* are tacked on to
the end of the retrieved array.
- type
- The type object used to instantiate a scalar of this data-type.
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
|
class errstate(__builtin__.object) |
| |
errstate(**kwargs)
Context manager for floating-point error handling.
Using an instance of `errstate` as a context manager allows statements in
that context to execute with a known error handling behavior. Upon entering
the context the error handling is set with `seterr` and `seterrcall`, and
upon exiting it is reset to what it was before.
Parameters
----------
kwargs : {divide, over, under, invalid}
Keyword arguments. The valid keywords are the possible floating-point
exceptions. Each keyword should have a string value that defines the
treatment for the particular error. Possible values are
{'ignore', 'warn', 'raise', 'call', 'print', 'log'}.
See Also
--------
seterr, geterr, seterrcall, geterrcall
Notes
-----
The ``with`` statement was introduced in Python 2.5, and can only be used
there by importing it: ``from __future__ import with_statement``. In
earlier Python versions the ``with`` statement is not available.
For complete documentation of the types of floating-point exceptions and
treatment options, see `seterr`.
Examples
--------
>>> from __future__ import with_statement # use 'with' in Python 2.5
>>> olderr = np.seterr(all='ignore') # Set error handling to known state.
>>> np.arange(3) / 0.
array([ NaN, Inf, Inf])
>>> with np.errstate(divide='warn'):
... np.arange(3) / 0.
...
__main__:2: RuntimeWarning: divide by zero encountered in divide
array([ NaN, Inf, Inf])
>>> np.sqrt(-1)
nan
>>> with np.errstate(invalid='raise'):
... np.sqrt(-1)
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
FloatingPointError: invalid value encountered in sqrt
Outside the context the error handling behavior has not changed:
>>> np.geterr()
{'over': 'ignore', 'divide': 'ignore', 'invalid': 'ignore',
'under': 'ignore'}
|
| |
Methods defined here:
- __enter__(self)
- __exit__(self, *exc_info)
- __init__(self, **kwargs)
- # Note that we don't want to run the above doctests because they will fail
# without a from __future__ import with_statement
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
|
class finfo(__builtin__.object) |
| |
finfo(dtype)
Machine limits for floating point types.
Attributes
----------
eps : floating point number of the appropriate type
The smallest representable number such that ``1.0 + eps != 1.0``.
epsneg : floating point number of the appropriate type
The smallest representable number such that ``1.0 - epsneg != 1.0``.
iexp : int
The number of bits in the exponent portion of the floating point
representation.
machar : MachAr
The object which calculated these parameters and holds more detailed
information.
machep : int
The exponent that yields ``eps``.
max : floating point number of the appropriate type
The largest representable number.
maxexp : int
The smallest positive power of the base (2) that causes overflow.
min : floating point number of the appropriate type
The smallest representable number, typically ``-max``.
minexp : int
The most negative power of the base (2) consistent with there being
no leading 0's in the mantissa.
negep : int
The exponent that yields ``epsneg``.
nexp : int
The number of bits in the exponent including its sign and bias.
nmant : int
The number of bits in the mantissa.
precision : int
The approximate number of decimal digits to which this kind of float
is precise.
resolution : floating point number of the appropriate type
The approximate decimal resolution of this type, i.e.
``10**-precision``.
tiny : floating point number of the appropriate type
The smallest-magnitude usable number.
Parameters
----------
dtype : floating point type, dtype, or instance
The kind of floating point data type to get information about.
See Also
--------
MachAr : The implementation of the tests that produce this information.
iinfo : The equivalent for integer data types.
Notes
-----
For developers of NumPy: do not instantiate this at the module level. The
initial calculation of these parameters is expensive and negatively impacts
import times. These objects are cached, so calling ``finfo()`` repeatedly
inside your functions is not a problem.
|
| |
Methods defined here:
- __str__(self)
Static methods defined here:
- __new__(cls, dtype)
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
|
class flatiter(__builtin__.object) |
| |
Flat iterator object to iterate over arrays.
A `flatiter` iterator is returned by ``x.flat`` for any array `x`.
It allows iterating over the array as if it were a 1-D array,
either in a for-loop or by calling its `next` method.
Iteration is done in C-contiguous style, with the last index varying the
fastest. The iterator can also be indexed using basic slicing or
advanced indexing.
See Also
--------
ndarray.flat : Return a flat iterator over an array.
ndarray.flatten : Returns a flattened copy of an array.
Notes
-----
A `flatiter` iterator can not be constructed directly from Python code
by calling the `flatiter` constructor.
Examples
--------
>>> x = np.arange(6).reshape(2, 3)
>>> fl = x.flat
>>> type(fl)
<type 'numpy.flatiter'>
>>> for item in fl:
... print item
...
0
1
2
3
4
5
>>> fl[2:4]
array([2, 3])
|
| |
Methods defined here:
- __array__(...)
- __array__(type=None) Get array from iterator
- __delitem__(...)
- x.__delitem__(y) <==> del x[y]
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __iter__(...)
- x.__iter__() <==> iter(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __len__(...)
- x.__len__() <==> len(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __setitem__(...)
- x.__setitem__(i, y) <==> x[i]=y
- copy(...)
- copy()
Get a copy of the iterator as a 1-D array.
Examples
--------
>>> x = np.arange(6).reshape(2, 3)
>>> x
array([[0, 1, 2],
[3, 4, 5]])
>>> fl = x.flat
>>> fl.copy()
array([0, 1, 2, 3, 4, 5])
- next(...)
- x.next() -> the next value, or raise StopIteration
Data descriptors defined here:
- base
- A reference to the array that is iterated over.
Examples
--------
>>> x = np.arange(5)
>>> fl = x.flat
>>> fl.base is x
True
- coords
- An N-dimensional tuple of current coordinates.
Examples
--------
>>> x = np.arange(6).reshape(2, 3)
>>> fl = x.flat
>>> fl.coords
(0, 0)
>>> fl.next()
0
>>> fl.coords
(0, 1)
- index
- Current flat index into the array.
Examples
--------
>>> x = np.arange(6).reshape(2, 3)
>>> fl = x.flat
>>> fl.index
0
>>> fl.next()
0
>>> fl.index
1
|
class flexible(generic) |
| | |
- Method resolution order:
- flexible
- generic
- __builtin__.object
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class float128(floating) |
| |
128-bit floating-point number. Character code: 'g'. C long float
compatible.
|
| |
- Method resolution order:
- float128
- floating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class float32(floating) |
| |
32-bit floating-point number. Character code 'f'. C float compatible.
|
| |
- Method resolution order:
- float32
- floating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class float64(floating, __builtin__.float) |
| |
64-bit floating-point number. Character code 'd'. Python float compatible.
|
| |
- Method resolution order:
- float64
- floating
- inexact
- number
- generic
- __builtin__.float
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.float:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- float.__format__(format_spec) -> string
Formats the float according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Returns the Integral closest to x between 0 and x.
- as_integer_ratio(...)
- float.as_integer_ratio() -> (int, int)
Returns a pair of integers, whose ratio is exactly equal to the original
float and with a positive denominator.
Raises OverflowError on infinities and a ValueError on NaNs.
>>> (10.0).as_integer_ratio()
(10, 1)
>>> (0.0).as_integer_ratio()
(0, 1)
>>> (-.25).as_integer_ratio()
(-1, 4)
- hex(...)
- float.hex() -> string
Return a hexadecimal representation of a floating-point number.
>>> (-0.1).hex()
'-0x1.999999999999ap-4'
>>> 3.14159.hex()
'0x1.921f9f01b866ep+1'
- is_integer(...)
- Returns True if the float is an integer.
Data and other attributes inherited from __builtin__.float:
- __getformat__ = <built-in method __getformat__ of type object>
- float.__getformat__(typestr) -> string
You probably don't want to use this function. It exists mainly to be
used in Python's test suite.
typestr must be 'double' or 'float'. This function returns whichever of
'unknown', 'IEEE, big-endian' or 'IEEE, little-endian' best describes the
format of floating point numbers used by the C type named by typestr.
- __setformat__ = <built-in method __setformat__ of type object>
- float.__setformat__(typestr, fmt) -> None
You probably don't want to use this function. It exists mainly to be
used in Python's test suite.
typestr must be 'double' or 'float'. fmt must be one of 'unknown',
'IEEE, big-endian' or 'IEEE, little-endian', and in addition can only be
one of the latter two if it appears to match the underlying C reality.
Overrides the automatic determination of C-level floating point type.
This affects how floats are converted to and from binary strings.
- fromhex = <built-in method fromhex of type object>
- float.fromhex(string) -> float
Create a floating-point number from a hexadecimal string.
>>> float.fromhex('0x1.ffffp10')
2047.984375
>>> float.fromhex('-0x1p-1074')
-4.9406564584124654e-324
|
float_ = class float64(floating, __builtin__.float) |
| |
64-bit floating-point number. Character code 'd'. Python float compatible.
|
| |
- Method resolution order:
- float64
- floating
- inexact
- number
- generic
- __builtin__.float
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.float:
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- float.__format__(format_spec) -> string
Formats the float according to format_spec.
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Returns the Integral closest to x between 0 and x.
- as_integer_ratio(...)
- float.as_integer_ratio() -> (int, int)
Returns a pair of integers, whose ratio is exactly equal to the original
float and with a positive denominator.
Raises OverflowError on infinities and a ValueError on NaNs.
>>> (10.0).as_integer_ratio()
(10, 1)
>>> (0.0).as_integer_ratio()
(0, 1)
>>> (-.25).as_integer_ratio()
(-1, 4)
- hex(...)
- float.hex() -> string
Return a hexadecimal representation of a floating-point number.
>>> (-0.1).hex()
'-0x1.999999999999ap-4'
>>> 3.14159.hex()
'0x1.921f9f01b866ep+1'
- is_integer(...)
- Returns True if the float is an integer.
Data and other attributes inherited from __builtin__.float:
- __getformat__ = <built-in method __getformat__ of type object>
- float.__getformat__(typestr) -> string
You probably don't want to use this function. It exists mainly to be
used in Python's test suite.
typestr must be 'double' or 'float'. This function returns whichever of
'unknown', 'IEEE, big-endian' or 'IEEE, little-endian' best describes the
format of floating point numbers used by the C type named by typestr.
- __setformat__ = <built-in method __setformat__ of type object>
- float.__setformat__(typestr, fmt) -> None
You probably don't want to use this function. It exists mainly to be
used in Python's test suite.
typestr must be 'double' or 'float'. fmt must be one of 'unknown',
'IEEE, big-endian' or 'IEEE, little-endian', and in addition can only be
one of the latter two if it appears to match the underlying C reality.
Overrides the automatic determination of C-level floating point type.
This affects how floats are converted to and from binary strings.
- fromhex = <built-in method fromhex of type object>
- float.fromhex(string) -> float
Create a floating-point number from a hexadecimal string.
>>> float.fromhex('0x1.ffffp10')
2047.984375
>>> float.fromhex('-0x1p-1074')
-4.9406564584124654e-324
|
class floating(inexact) |
| | |
- Method resolution order:
- floating
- inexact
- number
- generic
- __builtin__.object
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class format_parser |
| |
Class to convert formats, names, titles description to a dtype.
After constructing the format_parser object, the dtype attribute is
the converted data-type:
``dtype = format_parser(formats, names, titles).dtype``
Attributes
----------
dtype : dtype
The converted data-type.
Parameters
----------
formats : str or list of str
The format description, either specified as a string with
comma-separated format descriptions in the form ``'f8, i4, a5'``, or
a list of format description strings in the form
``['f8', 'i4', 'a5']``.
names : str or list/tuple of str
The field names, either specified as a comma-separated string in the
form ``'col1, col2, col3'``, or as a list or tuple of strings in the
form ``['col1', 'col2', 'col3']``.
An empty list can be used, in that case default field names
('f0', 'f1', ...) are used.
titles : sequence
Sequence of title strings. An empty list can be used to leave titles
out.
aligned : bool, optional
If True, align the fields by padding as the C-compiler would.
Default is False.
byteorder : str, optional
If specified, all the fields will be changed to the
provided byte-order. Otherwise, the default byte-order is
used. For all available string specifiers, see `dtype.newbyteorder`.
See Also
--------
dtype, typename, sctype2char
Examples
--------
>>> np.format_parser(['f8', 'i4', 'a5'], ['col1', 'col2', 'col3'],
... ['T1', 'T2', 'T3']).dtype
dtype([(('T1', 'col1'), '<f8'), (('T2', 'col2'), '<i4'),
(('T3', 'col3'), '|S5')])
`names` and/or `titles` can be empty lists. If `titles` is an empty list,
titles will simply not appear. If `names` is empty, default field names
will be used.
>>> np.format_parser(['f8', 'i4', 'a5'], ['col1', 'col2', 'col3'],
... []).dtype
dtype([('col1', '<f8'), ('col2', '<i4'), ('col3', '|S5')])
>>> np.format_parser(['f8', 'i4', 'a5'], [], []).dtype
dtype([('f0', '<f8'), ('f1', '<i4'), ('f2', '|S5')])
|
| |
Methods defined here:
- __init__(self, formats, names, titles, aligned=False, byteorder=None)
|
class generic(__builtin__.object) |
| |
Base class for numpy scalar types.
Class from which most (all?) numpy scalar types are derived. For
consistency, exposes the same API as `ndarray`, despite many
consequent attributes being either "get-only," or completely irrelevant.
This is the class from which it is strongly suggested users should derive
custom scalar types.
|
| |
Methods defined here:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors defined here:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class iinfo |
| |
iinfo(type)
Machine limits for integer types.
Attributes
----------
min : int
The smallest integer expressible by the type.
max : int
The largest integer expressible by the type.
Parameters
----------
type : integer type, dtype, or instance
The kind of integer data type to get information about.
See Also
--------
finfo : The equivalent for floating point data types.
Examples
--------
With types:
>>> ii16 = np.iinfo(np.int16)
>>> ii16.min
-32768
>>> ii16.max
32767
>>> ii32 = np.iinfo(np.int32)
>>> ii32.min
-2147483648
>>> ii32.max
2147483647
With instances:
>>> ii32 = np.iinfo(np.int32(10))
>>> ii32.min
-2147483648
>>> ii32.max
2147483647
|
| |
Methods defined here:
- __init__(self, int_type)
- __str__(self)
- String representation.
Data descriptors defined here:
- max
- Maximum value of given dtype.
- min
- Minimum value of given dtype.
|
class inexact(number) |
| | |
- Method resolution order:
- inexact
- number
- generic
- __builtin__.object
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
int0 = class int64(signedinteger, __builtin__.int) |
| |
64-bit integer. Character code 'l'. Python int compatible.
|
| |
- Method resolution order:
- int64
- signedinteger
- integer
- number
- generic
- __builtin__.int
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.int:
- __cmp__(...)
- x.__cmp__(y) <==> cmp(x,y)
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Truncating an Integral returns itself.
- bit_length(...)
- int.bit_length() -> int
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
Data descriptors inherited from __builtin__.int:
- denominator
- the denominator of a rational number in lowest terms
- numerator
- the numerator of a rational number in lowest terms
|
class int16(signedinteger) |
| |
16-bit integer. Character code ``h``. C short compatible.
|
| |
- Method resolution order:
- int16
- signedinteger
- integer
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class int32(signedinteger) |
| |
32-bit integer. Character code 'i'. C int compatible.
|
| |
- Method resolution order:
- int32
- signedinteger
- integer
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class int64(signedinteger, __builtin__.int) |
| |
64-bit integer. Character code 'l'. Python int compatible.
|
| |
- Method resolution order:
- int64
- signedinteger
- integer
- number
- generic
- __builtin__.int
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.int:
- __cmp__(...)
- x.__cmp__(y) <==> cmp(x,y)
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Truncating an Integral returns itself.
- bit_length(...)
- int.bit_length() -> int
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
Data descriptors inherited from __builtin__.int:
- denominator
- the denominator of a rational number in lowest terms
- numerator
- the numerator of a rational number in lowest terms
|
class int8(signedinteger) |
| |
8-bit integer. Character code ``b``. C char compatible.
|
| |
- Method resolution order:
- int8
- signedinteger
- integer
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
int_ = class int64(signedinteger, __builtin__.int) |
| |
64-bit integer. Character code 'l'. Python int compatible.
|
| |
- Method resolution order:
- int64
- signedinteger
- integer
- number
- generic
- __builtin__.int
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.int:
- __cmp__(...)
- x.__cmp__(y) <==> cmp(x,y)
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Truncating an Integral returns itself.
- bit_length(...)
- int.bit_length() -> int
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
Data descriptors inherited from __builtin__.int:
- denominator
- the denominator of a rational number in lowest terms
- numerator
- the numerator of a rational number in lowest terms
|
intc = class int32(signedinteger) |
| |
32-bit integer. Character code 'i'. C int compatible.
|
| |
- Method resolution order:
- int32
- signedinteger
- integer
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
class integer(number) |
| | |
- Method resolution order:
- integer
- number
- generic
- __builtin__.object
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
intp = class int64(signedinteger, __builtin__.int) |
| |
64-bit integer. Character code 'l'. Python int compatible.
|
| |
- Method resolution order:
- int64
- signedinteger
- integer
- number
- generic
- __builtin__.int
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.int:
- __cmp__(...)
- x.__cmp__(y) <==> cmp(x,y)
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Truncating an Integral returns itself.
- bit_length(...)
- int.bit_length() -> int
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
Data descriptors inherited from __builtin__.int:
- denominator
- the denominator of a rational number in lowest terms
- numerator
- the numerator of a rational number in lowest terms
|
longcomplex = class complex256(complexfloating) |
| |
Composed of two 128 bit floats
|
| |
- Method resolution order:
- complex256
- complexfloating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __complex__(...)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
longdouble = class float128(floating) |
| |
128-bit floating-point number. Character code: 'g'. C long float
compatible.
|
| |
- Method resolution order:
- float128
- floating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
longfloat = class float128(floating) |
| |
128-bit floating-point number. Character code: 'g'. C long float
compatible.
|
| |
- Method resolution order:
- float128
- floating
- inexact
- number
- generic
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hash__(...)
- x.__hash__() <==> hash(x)
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __le__(...)
- x.__le__(y) <==> x<=y
- __long__(...)
- x.__long__() <==> long(x)
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __oct__(...)
- x.__oct__() <==> oct(x)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __str__(...)
- x.__str__() <==> str(x)
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __invert__(...)
- x.__invert__() <==> ~x
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
|
longlong = class int64(signedinteger, __builtin__.int) |
| | |
- Method resolution order:
- int64
- signedinteger
- integer
- number
- generic
- __builtin__.int
- __builtin__.object
Methods defined here:
- __eq__(...)
- x.__eq__(y) <==> x==y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __gt__(...)
- x.__gt__(y) <==> x>y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __le__(...)
- x.__le__(y) <==> x<=y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __ne__(...)
- x.__ne__(y) <==> x!=y
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
Methods inherited from generic:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- sc.__array__(|type) return 0-dim array
- __array_wrap__(...)
- sc.__array_wrap__(obj) return scalar from array
- __copy__(...)
- __deepcopy__(...)
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __getitem__(...)
- x.__getitem__(y) <==> x[y]
- __hex__(...)
- x.__hex__() <==> hex(x)
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __mul__(...)
- x.__mul__(y) <==> x*y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __pow__(...)
- x.__pow__(y[, z]) <==> pow(x, y[, z])
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- __repr__(...)
- x.__repr__() <==> repr(x)
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __rmul__(...)
- x.__rmul__(y) <==> y*x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rpow__(...)
- y.__rpow__(x[, z]) <==> pow(x, y[, z])
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setstate__(...)
- __str__(...)
- x.__str__() <==> str(x)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- all(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- any(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmax(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argmin(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- argsort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- astype(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- byteswap(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- choose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- clip(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- compress(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- conj(...)
- conjugate(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- copy(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumprod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- cumsum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- diagonal(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dump(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- dumps(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- fill(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- flatten(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- getfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- item(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- itemset(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- max(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- mean(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- min(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- newbyteorder(...)
- newbyteorder(new_order='S')
Return a new `dtype` with a different byte order.
Changes are also made in all fields and sub-arrays of the data type.
The `new_order` code can be any from the following:
* {'<', 'L'} - little endian
* {'>', 'B'} - big endian
* {'=', 'N'} - native order
* 'S' - swap dtype from current to opposite endian
* {'|', 'I'} - ignore (no change to byte order)
Parameters
----------
new_order : str, optional
Byte order to force; a value from the byte order specifications
above. The default value ('S') results in swapping the current
byte order. The code does a case-insensitive check on the first
letter of `new_order` for the alternatives above. For example,
any of 'B' or 'b' or 'biggish' are valid to specify big-endian.
Returns
-------
new_dtype : dtype
New `dtype` object with the given change to the byte order.
- nonzero(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- prod(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ptp(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- put(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- ravel(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- repeat(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- reshape(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- resize(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- round(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- searchsorted(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setfield(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- setflags(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class so as to
provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sort(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- squeeze(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- std(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- sum(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- swapaxes(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- take(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tofile(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tolist(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- tostring(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- trace(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- transpose(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- var(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
- view(...)
- Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
Data descriptors inherited from generic:
- T
- transpose
- __array_interface__
- Array protocol: Python side
- __array_priority__
- Array priority.
- __array_struct__
- Array protocol: struct
- base
- base object
- data
- pointer to start of data
- dtype
- get array data-descriptor
- flags
- integer value of flags
- flat
- a 1-d view of scalar
- imag
- imaginary part of scalar
- itemsize
- length of one element in bytes
- nbytes
- length of item in bytes
- ndim
- number of array dimensions
- real
- real part of scalar
- shape
- tuple of array dimensions
- size
- number of elements in the gentype
- strides
- tuple of bytes steps in each dimension
Methods inherited from __builtin__.int:
- __cmp__(...)
- x.__cmp__(y) <==> cmp(x,y)
- __coerce__(...)
- x.__coerce__(y) <==> coerce(x, y)
- __format__(...)
- __getattribute__(...)
- x.__getattribute__('name') <==> x.name
- __getnewargs__(...)
- __hash__(...)
- x.__hash__() <==> hash(x)
- __trunc__(...)
- Truncating an Integral returns itself.
- bit_length(...)
- int.bit_length() -> int
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
Data descriptors inherited from __builtin__.int:
- denominator
- the denominator of a rational number in lowest terms
- numerator
- the numerator of a rational number in lowest terms
|
class matrix(numpy.ndarray) |
| |
matrix(data, dtype=None, copy=True)
Returns a matrix from an array-like object, or from a string of data.
A matrix is a specialized 2-D array that retains its 2-D nature
through operations. It has certain special operators, such as ``*``
(matrix multiplication) and ``**`` (matrix power).
Parameters
----------
data : array_like or string
If `data` is a string, it is interpreted as a matrix with commas
or spaces separating columns, and semicolons separating rows.
dtype : data-type
Data-type of the output matrix.
copy : bool
If `data` is already an `ndarray`, then this flag determines
whether the data is copied (the default), or whether a view is
constructed.
See Also
--------
array
Examples
--------
>>> a = np.matrix('1 2; 3 4')
>>> print a
[[1 2]
[3 4]]
>>> np.matrix([[1, 2], [3, 4]])
matrix([[1, 2],
[3, 4]])
|
| |
- Method resolution order:
- matrix
- numpy.ndarray
- __builtin__.object
Methods defined here:
- __array_finalize__(self, obj)
- __getitem__(self, index)
- __imul__(self, other)
- __ipow__(self, other)
- __mul__(self, other)
- __pow__(self, other)
- __repr__(self)
- __rmul__(self, other)
- __rpow__(self, other)
- __str__(self)
- all(self, axis=None, out=None)
- Test whether all matrix elements along a given axis evaluate to True.
Parameters
----------
See `numpy.all` for complete descriptions
See Also
--------
numpy.all
Notes
-----
This is the same as `ndarray.all`, but it returns a `matrix` object.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> y = x[0]; y
matrix([[0, 1, 2, 3]])
>>> (x == y)
matrix([[ True, True, True, True],
[False, False, False, False],
[False, False, False, False]], dtype=bool)
>>> (x == y).all()
False
>>> (x == y).all(0)
matrix([[False, False, False, False]], dtype=bool)
>>> (x == y).all(1)
matrix([[ True],
[False],
[False]], dtype=bool)
- any(self, axis=None, out=None)
- Test whether any array element along a given axis evaluates to True.
Refer to `numpy.any` for full documentation.
Parameters
----------
axis: int, optional
Axis along which logical OR is performed
out: ndarray, optional
Output to existing array instead of creating new one, must have
same shape as expected output
Returns
-------
any : bool, ndarray
Returns a single bool if `axis` is ``None``; otherwise,
returns `ndarray`
- argmax(self, axis=None, out=None)
- Indices of the maximum values along an axis.
Parameters
----------
See `numpy.argmax` for complete descriptions
See Also
--------
numpy.argmax
Notes
-----
This is the same as `ndarray.argmax`, but returns a `matrix` object
where `ndarray.argmax` would return an `ndarray`.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.argmax()
11
>>> x.argmax(0)
matrix([[2, 2, 2, 2]])
>>> x.argmax(1)
matrix([[3],
[3],
[3]])
- argmin(self, axis=None, out=None)
- Return the indices of the minimum values along an axis.
Parameters
----------
See `numpy.argmin` for complete descriptions.
See Also
--------
numpy.argmin
Notes
-----
This is the same as `ndarray.argmin`, but returns a `matrix` object
where `ndarray.argmin` would return an `ndarray`.
Examples
--------
>>> x = -np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, -1, -2, -3],
[ -4, -5, -6, -7],
[ -8, -9, -10, -11]])
>>> x.argmin()
11
>>> x.argmin(0)
matrix([[2, 2, 2, 2]])
>>> x.argmin(1)
matrix([[3],
[3],
[3]])
- getA(self)
- Return `self` as an `ndarray` object.
Equivalent to ``np.asarray(self)``.
Parameters
----------
None
Returns
-------
ret : ndarray
`self` as an `ndarray`
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.getA()
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
- getA1(self)
- Return `self` as a flattened `ndarray`.
Equivalent to ``np.asarray(x).ravel()``
Parameters
----------
None
Returns
-------
ret : ndarray
`self`, 1-D, as an `ndarray`
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.getA1()
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
- getH(self)
- Returns the (complex) conjugate transpose of `self`.
Equivalent to ``np.transpose(self)`` if `self` is real-valued.
Parameters
----------
None
Returns
-------
ret : matrix object
complex conjugate transpose of `self`
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4)))
>>> z = x - 1j*x; z
matrix([[ 0. +0.j, 1. -1.j, 2. -2.j, 3. -3.j],
[ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j],
[ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]])
>>> z.getH()
matrix([[ 0. +0.j, 4. +4.j, 8. +8.j],
[ 1. +1.j, 5. +5.j, 9. +9.j],
[ 2. +2.j, 6. +6.j, 10.+10.j],
[ 3. +3.j, 7. +7.j, 11.+11.j]])
- getI(self)
- Returns the (multiplicative) inverse of invertible `self`.
Parameters
----------
None
Returns
-------
ret : matrix object
If `self` is non-singular, `ret` is such that ``ret * self`` ==
``self * ret`` == ``np.matrix(np.eye(self[0,:].size)`` all return
``True``.
Raises
------
numpy.linalg.linalg.LinAlgError: Singular matrix
If `self` is singular.
See Also
--------
linalg.inv
Examples
--------
>>> m = np.matrix('[1, 2; 3, 4]'); m
matrix([[1, 2],
[3, 4]])
>>> m.getI()
matrix([[-2. , 1. ],
[ 1.5, -0.5]])
>>> m.getI() * m
matrix([[ 1., 0.],
[ 0., 1.]])
- getT(self)
- Returns the transpose of the matrix.
Does *not* conjugate! For the complex conjugate transpose, use `getH`.
Parameters
----------
None
Returns
-------
ret : matrix object
The (non-conjugated) transpose of the matrix.
See Also
--------
transpose, getH
Examples
--------
>>> m = np.matrix('[1, 2; 3, 4]')
>>> m
matrix([[1, 2],
[3, 4]])
>>> m.getT()
matrix([[1, 3],
[2, 4]])
- max(self, axis=None, out=None)
- Return the maximum value along an axis.
Parameters
----------
See `amax` for complete descriptions
See Also
--------
amax, ndarray.max
Notes
-----
This is the same as `ndarray.max`, but returns a `matrix` object
where `ndarray.max` would return an ndarray.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.max()
11
>>> x.max(0)
matrix([[ 8, 9, 10, 11]])
>>> x.max(1)
matrix([[ 3],
[ 7],
[11]])
- mean(self, axis=None, dtype=None, out=None)
- Returns the average of the matrix elements along the given axis.
Refer to `numpy.mean` for full documentation.
See Also
--------
numpy.mean
Notes
-----
Same as `ndarray.mean` except that, where that returns an `ndarray`,
this returns a `matrix` object.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3, 4)))
>>> x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.mean()
5.5
>>> x.mean(0)
matrix([[ 4., 5., 6., 7.]])
>>> x.mean(1)
matrix([[ 1.5],
[ 5.5],
[ 9.5]])
- min(self, axis=None, out=None)
- Return the minimum value along an axis.
Parameters
----------
See `amin` for complete descriptions.
See Also
--------
amin, ndarray.min
Notes
-----
This is the same as `ndarray.min`, but returns a `matrix` object
where `ndarray.min` would return an ndarray.
Examples
--------
>>> x = -np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, -1, -2, -3],
[ -4, -5, -6, -7],
[ -8, -9, -10, -11]])
>>> x.min()
-11
>>> x.min(0)
matrix([[ -8, -9, -10, -11]])
>>> x.min(1)
matrix([[ -3],
[ -7],
[-11]])
- prod(self, axis=None, dtype=None, out=None)
- Return the product of the array elements over the given axis.
Refer to `prod` for full documentation.
See Also
--------
prod, ndarray.prod
Notes
-----
Same as `ndarray.prod`, except, where that returns an `ndarray`, this
returns a `matrix` object instead.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.prod()
0
>>> x.prod(0)
matrix([[ 0, 45, 120, 231]])
>>> x.prod(1)
matrix([[ 0],
[ 840],
[7920]])
- ptp(self, axis=None, out=None)
- Peak-to-peak (maximum - minimum) value along the given axis.
Refer to `numpy.ptp` for full documentation.
See Also
--------
numpy.ptp
Notes
-----
Same as `ndarray.ptp`, except, where that would return an `ndarray` object,
this returns a `matrix` object.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.ptp()
11
>>> x.ptp(0)
matrix([[8, 8, 8, 8]])
>>> x.ptp(1)
matrix([[3],
[3],
[3]])
- std(self, axis=None, dtype=None, out=None, ddof=0)
- Return the standard deviation of the array elements along the given axis.
Refer to `numpy.std` for full documentation.
See Also
--------
numpy.std
Notes
-----
This is the same as `ndarray.std`, except that where an `ndarray` would
be returned, a `matrix` object is returned instead.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3, 4)))
>>> x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.std()
3.4520525295346629
>>> x.std(0)
matrix([[ 3.26598632, 3.26598632, 3.26598632, 3.26598632]])
>>> x.std(1)
matrix([[ 1.11803399],
[ 1.11803399],
[ 1.11803399]])
- sum(self, axis=None, dtype=None, out=None)
- Returns the sum of the matrix elements, along the given axis.
Refer to `numpy.sum` for full documentation.
See Also
--------
numpy.sum
Notes
-----
This is the same as `ndarray.sum`, except that where an `ndarray` would
be returned, a `matrix` object is returned instead.
Examples
--------
>>> x = np.matrix([[1, 2], [4, 3]])
>>> x.sum()
10
>>> x.sum(axis=1)
matrix([[3],
[7]])
>>> x.sum(axis=1, dtype='float')
matrix([[ 3.],
[ 7.]])
>>> out = np.zeros((1, 2), dtype='float')
>>> x.sum(axis=1, dtype='float', out=out)
matrix([[ 3.],
[ 7.]])
- tolist(self)
- Return the matrix as a (possibly nested) list.
See `ndarray.tolist` for full documentation.
See Also
--------
ndarray.tolist
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4))); x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.tolist()
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]
- var(self, axis=None, dtype=None, out=None, ddof=0)
- Returns the variance of the matrix elements, along the given axis.
Refer to `numpy.var` for full documentation.
See Also
--------
numpy.var
Notes
-----
This is the same as `ndarray.var`, except that where an `ndarray` would
be returned, a `matrix` object is returned instead.
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3, 4)))
>>> x
matrix([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
>>> x.var()
11.916666666666666
>>> x.var(0)
matrix([[ 10.66666667, 10.66666667, 10.66666667, 10.66666667]])
>>> x.var(1)
matrix([[ 1.25],
[ 1.25],
[ 1.25]])
Static methods defined here:
- __new__(subtype, data, dtype=None, copy=True)
Data descriptors defined here:
- A
- base array
- A1
- 1-d base array
- H
- hermitian (conjugate) transpose
- I
- inverse
- T
- transpose
- __dict__
- dictionary for instance variables (if defined)
Data and other attributes defined here:
- __array_priority__ = 10.0
Methods inherited from numpy.ndarray:
- __abs__(...)
- x.__abs__() <==> abs(x)
- __add__(...)
- x.__add__(y) <==> x+y
- __and__(...)
- x.__and__(y) <==> x&y
- __array__(...)
- a.__array__(|dtype) -> reference if type unchanged, copy otherwise.
Returns either a new reference to self if dtype is not given or a new array
of provided data type if dtype is different from the current dtype of the
array.
- __array_prepare__(...)
- a.__array_prepare__(obj) -> Object of same type as ndarray object obj.
- __array_wrap__(...)
- a.__array_wrap__(obj) -> Object of same type as ndarray object a.
- __contains__(...)
- x.__contains__(y) <==> y in x
- __copy__(...)
- a.__copy__([order])
Return a copy of the array.
Parameters
----------
order : {'C', 'F', 'A'}, optional
If order is 'C' (False) then the result is contiguous (default).
If order is 'Fortran' (True) then the result has fortran order.
If order is 'Any' (None) then the result has fortran order
only if the array already is in fortran order.
- __deepcopy__(...)
- a.__deepcopy__() -> Deep copy of array.
Used if copy.deepcopy is called on an array.
- __delitem__(...)
- x.__delitem__(y) <==> del x[y]
- __delslice__(...)
- x.__delslice__(i, j) <==> del x[i:j]
Use of negative indices is not supported.
- __div__(...)
- x.__div__(y) <==> x/y
- __divmod__(...)
- x.__divmod__(y) <==> divmod(x, y)
- __eq__(...)
- x.__eq__(y) <==> x==y
- __float__(...)
- x.__float__() <==> float(x)
- __floordiv__(...)
- x.__floordiv__(y) <==> x//y
- __ge__(...)
- x.__ge__(y) <==> x>=y
- __getslice__(...)
- x.__getslice__(i, j) <==> x[i:j]
Use of negative indices is not supported.
- __gt__(...)
- x.__gt__(y) <==> x>y
- __hex__(...)
- x.__hex__() <==> hex(x)
- __iadd__(...)
- x.__iadd__(y) <==> x+y
- __iand__(...)
- x.__iand__(y) <==> x&y
- __idiv__(...)
- x.__idiv__(y) <==> x/y
- __ifloordiv__(...)
- x.__ifloordiv__(y) <==> x//y
- __ilshift__(...)
- x.__ilshift__(y) <==> x<<y
- __imod__(...)
- x.__imod__(y) <==> x%y
- __index__(...)
- x[y:z] <==> x[y.__index__():z.__index__()]
- __int__(...)
- x.__int__() <==> int(x)
- __invert__(...)
- x.__invert__() <==> ~x
- __ior__(...)
- x.__ior__(y) <==> x|y
- __irshift__(...)
- x.__irshift__(y) <==> x>>y
- __isub__(...)
- x.__isub__(y) <==> x-y
- __iter__(...)
- x.__iter__() <==> iter(x)
- __itruediv__(...)
- x.__itruediv__(y) <==> x/y
- __ixor__(...)
- x.__ixor__(y) <==> x^y
- __le__(...)
- x.__le__(y) <==> x<=y
- __len__(...)
- x.__len__() <==> len(x)
- __long__(...)
- x.__long__() <==> long(x)
- __lshift__(...)
- x.__lshift__(y) <==> x<<y
- __lt__(...)
- x.__lt__(y) <==> x<y
- __mod__(...)
- x.__mod__(y) <==> x%y
- __ne__(...)
- x.__ne__(y) <==> x!=y
- __neg__(...)
- x.__neg__() <==> -x
- __nonzero__(...)
- x.__nonzero__() <==> x != 0
- __oct__(...)
- x.__oct__() <==> oct(x)
- __or__(...)
- x.__or__(y) <==> x|y
- __pos__(...)
- x.__pos__() <==> +x
- __radd__(...)
- x.__radd__(y) <==> y+x
- __rand__(...)
- x.__rand__(y) <==> y&x
- __rdiv__(...)
- x.__rdiv__(y) <==> y/x
- __rdivmod__(...)
- x.__rdivmod__(y) <==> divmod(y, x)
- __reduce__(...)
- a.__reduce__()
For pickling.
- __rfloordiv__(...)
- x.__rfloordiv__(y) <==> y//x
- __rlshift__(...)
- x.__rlshift__(y) <==> y<<x
- __rmod__(...)
- x.__rmod__(y) <==> y%x
- __ror__(...)
- x.__ror__(y) <==> y|x
- __rrshift__(...)
- x.__rrshift__(y) <==> y>>x
- __rshift__(...)
- x.__rshift__(y) <==> x>>y
- __rsub__(...)
- x.__rsub__(y) <==> y-x
- __rtruediv__(...)
- x.__rtruediv__(y) <==> y/x
- __rxor__(...)
- x.__rxor__(y) <==> y^x
- __setitem__(...)
- x.__setitem__(i, y) <==> x[i]=y
- __setslice__(...)
- x.__setslice__(i, j, y) <==> x[i:j]=y
Use of negative indices is not supported.
- __setstate__(...)
- a.__setstate__(version, shape, dtype, isfortran, rawdata)
For unpickling.
Parameters
----------
version : int
optional pickle version. If omitted defaults to 0.
shape : tuple
dtype : data-type
isFortran : bool
rawdata : string or list
a binary string with the data (or a list if 'a' is an object array)
- __sub__(...)
- x.__sub__(y) <==> x-y
- __truediv__(...)
- x.__truediv__(y) <==> x/y
- __xor__(...)
- x.__xor__(y) <==> x^y
- argsort(...)
- a.argsort(axis=-1, kind='quicksort', order=None)
Returns the indices that would sort this array.
Refer to `numpy.argsort` for full documentation.
See Also
--------
numpy.argsort : equivalent function
- astype(...)
- a.astype(t)
Copy of the array, cast to a specified type.
Parameters
----------
t : string or dtype
Typecode or data-type to which the array is cast.
Examples
--------
>>> x = np.array([1, 2, 2.5])
>>> x
array([ 1. , 2. , 2.5])
>>> x.astype(int)
array([1, 2, 2])
- byteswap(...)
- a.byteswap(inplace)
Swap the bytes of the array elements
Toggle between low-endian and big-endian data representation by
returning a byteswapped array, optionally swapped in-place.
Parameters
----------
inplace: bool, optional
If ``True``, swap bytes in-place, default is ``False``.
Returns
-------
out: ndarray
The byteswapped array. If `inplace` is ``True``, this is
a view to self.
Examples
--------
>>> A = np.array([1, 256, 8755], dtype=np.int16)
>>> map(hex, A)
['0x1', '0x100', '0x2233']
>>> A.byteswap(True)
array([ 256, 1, 13090], dtype=int16)
>>> map(hex, A)
['0x100', '0x1', '0x3322']
Arrays of strings are not swapped
>>> A = np.array(['ceg', 'fac'])
>>> A.byteswap()
array(['ceg', 'fac'],
dtype='|S3')
- choose(...)
- a.choose(choices, out=None, mode='raise')
Use an index array to construct a new array from a set of choices.
Refer to `numpy.choose` for full documentation.
See Also
--------
numpy.choose : equivalent function
- clip(...)
- a.clip(a_min, a_max, out=None)
Return an array whose values are limited to ``[a_min, a_max]``.
Refer to `numpy.clip` for full documentation.
See Also
--------
numpy.clip : equivalent function
- compress(...)
- a.compress(condition, axis=None, out=None)
Return selected slices of this array along given axis.
Refer to `numpy.compress` for full documentation.
See Also
--------
numpy.compress : equivalent function
- conj(...)
- a.conj()
Complex-conjugate all elements.
Refer to `numpy.conjugate` for full documentation.
See Also
--------
numpy.conjugate : equivalent function
- conjugate(...)
- a.conjugate()
Return the complex conjugate, element-wise.
Refer to `numpy.conjugate` for full documentation.
See Also
--------
numpy.conjugate : equivalent function
- copy(...)
- a.copy(order='C')
Return a copy of the array.
Parameters
----------
order : {'C', 'F', 'A'}, optional
By default, the result is stored in C-contiguous (row-major) order in
memory. If `order` is `F`, the result has 'Fortran' (column-major)
order. If order is 'A' ('Any'), then the result has the same order
as the input.
Examples
--------
>>> x = np.array([[1,2,3],[4,5,6]], order='F')
>>> y = x.copy()
>>> x.fill(0)
>>> x
array([[0, 0, 0],
[0, 0, 0]])
>>> y
array([[1, 2, 3],
[4, 5, 6]])
>>> y.flags['C_CONTIGUOUS']
True
- cumprod(...)
- a.cumprod(axis=None, dtype=None, out=None)
Return the cumulative product of the elements along the given axis.
Refer to `numpy.cumprod` for full documentation.
See Also
--------
numpy.cumprod : equivalent function
- cumsum(...)
- a.cumsum(axis=None, dtype=None, out=None)
Return the cumulative sum of the elements along the given axis.
Refer to `numpy.cumsum` for full documentation.
See Also
--------
numpy.cumsum : equivalent function
- diagonal(...)
- a.diagonal(offset=0, axis1=0, axis2=1)
Return specified diagonals.
Refer to `numpy.diagonal` for full documentation.
See Also
--------
numpy.diagonal : equivalent function
- dot(...)
- dump(...)
- a.dump(file)
Dump a pickle of the array to the specified file.
The array can be read back with pickle.load or numpy.load.
Parameters
----------
file : str
A string naming the dump file.
- dumps(...)
- a.dumps()
Returns the pickle of the array as a string.
pickle.loads or numpy.loads will convert the string back to an array.
Parameters
----------
None
- fill(...)
- a.fill(value)
Fill the array with a scalar value.
Parameters
----------
value : scalar
All elements of `a` will be assigned this value.
Examples
--------
>>> a = np.array([1, 2])
>>> a.fill(0)
>>> a
array([0, 0])
>>> a = np.empty(2)
>>> a.fill(1)
>>> a
array([ 1., 1.])
- flatten(...)
- a.flatten(order='C')
Return a copy of the array collapsed into one dimension.
Parameters
----------
order : {'C', 'F'}, optional
Whether to flatten in C (row-major) or Fortran (column-major) order.
The default is 'C'.
Returns
-------
y : ndarray
A copy of the input array, flattened to one dimension.
See Also
--------
ravel : Return a flattened array.
flat : A 1-D flat iterator over the array.
Examples
--------
>>> a = np.array([[1,2], [3,4]])
>>> a.flatten()
array([1, 2, 3, 4])
>>> a.flatten('F')
array([1, 3, 2, 4])
- getfield(...)
- a.getfield(dtype, offset)
Returns a field of the given array as a certain type.
A field is a view of the array data with each itemsize determined
by the given type and the offset into the current array, i.e. from
``offset * dtype.itemsize`` to ``(offset+1) * dtype.itemsize``.
Parameters
----------
dtype : str
String denoting the data type of the field.
offset : int
Number of `dtype.itemsize`'s to skip before beginning the element view.
Examples
--------
>>> x = np.diag([1.+1.j]*2)
>>> x
array([[ 1.+1.j, 0.+0.j],
[ 0.+0.j, 1.+1.j]])
>>> x.dtype
dtype('complex128')
>>> x.getfield('complex64', 0) # Note how this != x
array([[ 0.+1.875j, 0.+0.j ],
[ 0.+0.j , 0.+1.875j]], dtype=complex64)
>>> x.getfield('complex64',1) # Note how different this is than x
array([[ 0. +5.87173204e-39j, 0. +0.00000000e+00j],
[ 0. +0.00000000e+00j, 0. +5.87173204e-39j]], dtype=complex64)
>>> x.getfield('complex128', 0) # == x
array([[ 1.+1.j, 0.+0.j],
[ 0.+0.j, 1.+1.j]])
If the argument dtype is the same as x.dtype, then offset != 0 raises
a ValueError:
>>> x.getfield('complex128', 1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: Need 0 <= offset <= 0 for requested type but received offset = 1
>>> x.getfield('float64', 0)
array([[ 1., 0.],
[ 0., 1.]])
>>> x.getfield('float64', 1)
array([[ 1.77658241e-307, 0.00000000e+000],
[ 0.00000000e+000, 1.77658241e-307]])
- item(...)
- a.item(*args)
Copy an element of an array to a standard Python scalar and return it.
Parameters
----------
\*args : Arguments (variable number and type)
* none: in this case, the method only works for arrays
with one element (`a.size == 1`), which element is
copied into a standard Python scalar object and returned.
* int_type: this argument is interpreted as a flat index into
the array, specifying which element to copy and return.
* tuple of int_types: functions as does a single int_type argument,
except that the argument is interpreted as an nd-index into the
array.
Returns
-------
z : Standard Python scalar object
A copy of the specified element of the array as a suitable
Python scalar
Notes
-----
When the data type of `a` is longdouble or clongdouble, item() returns
a scalar array object because there is no available Python scalar that
would not lose information. Void arrays return a buffer object for item(),
unless fields are defined, in which case a tuple is returned.
`item` is very similar to a[args], except, instead of an array scalar,
a standard Python scalar is returned. This can be useful for speeding up
access to elements of the array and doing arithmetic on elements of the
array using Python's optimized math.
Examples
--------
>>> x = np.random.randint(9, size=(3, 3))
>>> x
array([[3, 1, 7],
[2, 8, 3],
[8, 5, 3]])
>>> x.item(3)
2
>>> x.item(7)
5
>>> x.item((0, 1))
1
>>> x.item((2, 2))
3
- itemset(...)
- a.itemset(*args)
Insert scalar into an array (scalar is cast to array's dtype, if possible)
There must be at least 1 argument, and define the last argument
as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster
than ``a[args] = item``. The item should be a scalar value and `args`
must select a single item in the array `a`.
Parameters
----------
\*args : Arguments
If one argument: a scalar, only used in case `a` is of size 1.
If two arguments: the last argument is the value to be set
and must be a scalar, the first argumen
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